An Integrated Framework To Improve The Concept Of Resource Specialisation.

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Distance-based accessibility indices

The paper attempts to develop a suitable accessibility index for networks where each link has a value such that a smaller number is preferred like distance, cost, or travel time. A measure called distance sum is characterized by three independent properties: anonymity, an appropriately chosen independence axiom, and dominance preservation, which requires that a node not far to any other is at least as accessible. We argue for the need of eliminating the independence property in certain applications. Therefore generalized distance sum, a family of accessibility indices, will be suggested. It is linear, considers the accessibility of vertices besides their distances and depends on a parameter in order to control its deviation from distance sum. Generalized distance sum is anonymous and satisfies dominance preservation if its parameter meets a sufficient condition. Two detailed examples demonstrate its ability to reflect the vulnerability of accessibility to link disruptions.

Local Distance-Based Generalized Linear Models using the dbstats package for R

This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

Bootstrapping pairs in Distance-Based Regression

La regressió basada en distàncies és un mètode de predicció que consisteix en dos passos: a partir de les distàncies entre observacions obtenim les variables latents, les quals passen a ser els regressors en un model lineal de mínims quadrats ordinaris. Les distàncies les calculem a partir dels predictors originals fent us d'una funció de dissimilaritats adequada. Donat que, en general, els regressors estan relacionats de manera no lineal amb la resposta, la seva selecció amb el test F usual no és possible. En aquest treball proposem una solució a aquest problema de selecció de predictors definint tests estadístics generalitzats i adaptant un mètode de bootstrap no paramètric per a l'estimació dels p-valors. Incluim un exemple numèric amb dades de l'assegurança d'automòbils.

Development and validation of a symptom-based activity index for adults with eosinophilic esophagitis.

BACKGROUND & AIMS: Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE) and to provide end points for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patient assessments of disease severity. We also evaluated relationships between patient assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings. METHODS: We collected information from 186 patients with EoE in Switzerland and the United States (69.4% male; median age, 43 y) via surveys (n = 135), focus groups (n = 27), and semistructured interviews (n = 24). Items were generated for the instruments to assess biologic activity based on physician input. Linear regression was used to quantify the extent to which variations in patient-reported disease characteristics could account for variations in patient assessment of EoE severity. The PRO instrument was used prospectively in 153 adult patients with EoE (72.5% male; median age, 38 y), and validated in an independent group of 120 patients with EoE (60.8% male; median age, 40.5 y). RESULTS: Seven PRO factors that are used to assess characteristics of dysphagia, behavioral adaptations to living with dysphagia, and pain while swallowing accounted for 67% of the variation in patient assessment of disease severity. Based on statistical consideration and patient input, a 7-day recall period was selected. Highly active EoE, based on endoscopic and histologic findings, was associated with an increase in patient-assessed disease severity. In the validation study, the mean difference between patient assessment of EoE severity (range, 0-10) and PRO score (range, 0-8.52) was 0.15. CONCLUSIONS: We developed and validated an EoE scoring system based on 7 PRO items that assess symptoms over a 7-day recall period. Clinicaltrials.gov number: NCT00939263.

Bootstrapping pairs in Distance-Based Regression

La regressió basada en distàncies és un mètode de predicció que consisteix en dos passos: a partir de les distàncies entre observacions obtenim les variables latents, les quals passen a ser els regressors en un model lineal de mínims quadrats ordinaris. Les distàncies les calculem a partir dels predictors originals fent us d'una funció de dissimilaritats adequada. Donat que, en general, els regressors estan relacionats de manera no lineal amb la resposta, la seva selecció amb el test F usual no és possible. En aquest treball proposem una solució a aquest problema de selecció de predictors definint tests estadístics generalitzats i adaptant un mètode de bootstrap no paramètric per a l'estimació dels p-valors. Incluim un exemple numèric amb dades de l'assegurança d'automòbils.

MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests

Context: Variation in photosynthetic activity of trees induced by climatic stress can be effectively evaluated using remote sensing data. Although adverse effects of climate on temperate forests have been subjected to increased scrutiny, the suitability of remote sensing imagery for identification of drought stress in such forests has not been explored fully. Aim: To evaluate the sensitivity of MODIS-based vegetation index to heat and drought stress in temperate forests, and explore the differences in stress response of oaks and beech. Methods: We identified 8 oak and 13 beech pure and mature stands, each covering between 4 and 13 MODIS pixels. For each pixel, we extracted a time series of MODIS NDVI from 2000 to 2010. We identified all sequences of continuous unseasonal NDVI decline to be used as the response variable indicative of environmental stress. Neural Networks-based regression modelling was then applied to identify the climatic variables that best explain observed NDVI declines. Results: Tested variables explained 84–97% of the variation in NDVI, whilst air temperature-related climate extremes were found to be the most influential. Beech showed a linear response to the most influential climatic predictors, while oak responded in a unimodal pattern suggesting a better coping mechanism. Conclusions: MODIS NDVI has proved sufficiently sensitive as a stand-level indicator of climatic stress acting upon temperate broadleaf forests, leading to its potential use in predicting drought stress from meteorological observations and improving parameterisation of forest stress indices.

Distance-based kriging relying on proxy simulations for inverse conditioning

Let us consider a large set of candidate parameter fields, such as hydraulic conductivity maps, on which we can run an accurate forward flow and transport simulation. We address the issue of rapidly identifying a subset of candidates whose response best match a reference response curve. In order to keep the number of calls to the accurate flow simulator computationally tractable, a recent distance-based approach relying on fast proxy simulations is revisited, and turned into a non-stationary kriging method where the covariance kernel is obtained by combining a classical kernel with the proxy. Once the accurate simulator has been run for an initial subset of parameter fields and a kriging metamodel has been inferred, the predictive distributions of misfits for the remaining parameter fields can be used as a guide to select candidate parameter fields in a sequential way. The proposed algorithm, Proxy-based Kriging for Sequential Inversion (ProKSI), relies on a variant of the Expected Improvement, a popular criterion for kriging-based global optimization. A statistical benchmark of ProKSI’s performances illustrates the efficiency and the robustness of the approach when using different kinds of proxies.

Development and Validation of a Symptom-Based Activity Index for Adults with Eosinophilic Esophagitis

BACKGROUND & Aims: Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE), to provide endpoints for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patients' assessments of disease severity. We also evaluated relationships between patients' assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings. METHODS We collected information from 186 patients with EoE in Switzerland and the US (69.4% male; median age, 43 years) via surveys (n = 135), focus groups (n = 27), and semi-structured interviews (n = 24). Items were generated for the instruments to assess biologic activity based on physician input. Linear regression was used to quantify the extent to which variations in patient-reported disease characteristics could account for variations in patients' assessment of EoE severity. The PRO instrument was prospectively used in 153 adult patients with EoE (72.5% male; median age, 38 years), and validated in an independent group of 120 patients with EoE (60.8% male; median age, 40.5 years). RESULTS Seven PRO factors that are used to assess characteristics of dysphagia, behavioral adaptations to living with dysphagia, and pain while swallowing accounted for 67% of the variation in patients' assessment of disease severity. Based on statistical consideration and patient input, a 7-day recall period was selected. Highly active EoE, based on endoscopic and histologic findings, was associated with an increase in patient-assessed disease severity. In the validation study, the mean difference between patient assessment of EoE severity and PRO score was 0.13 (on a scale from 0 to 10). CONCLUSIONS We developed and validated an EoE scoring system based on 7 PRO items that assesses symptoms over a 7-day recall period. Clinicaltrials.gov number: NCT00939263.

Evaluating perspectives for PRRS virus elimination from pig dense areas with a risk factor based herd index

Porcine reproductive and respiratory syndrome virus (PRRSV) is wide-spread in pig populations globally. In many regions of Europe with intensive pig production and high herd densities, the virus is endemic and can cause disease and production losses. This fuels discussion about the feasibility and sustainability of virus elimination from larger geographic regions. The implementation of a program aiming at virus elimination for areas with high pig density is unprecedented and its potential success is unknown. The objective of this work was to approach pig population data with a simple method that could support assessing the feasibility of a sustainable regional PRRSV elimination. Based on known risk factors such as pig herd structure and neighborhood conditions, an index characterizing individual herds' potential for endemic virus circulation and reinfection was designed. This index was subsequently used to compare data of all pig herds in two regions with different pig- and herd-densities in Lower Saxony (North-West Germany) where PRRSV is endemic. Distribution of the indexed herds was displayed using GIS. Clusters of high herd index densities forming potential risk hot spots were identified which could represent key target areas for surveillance and biosecurity measures under a control program aimed at virus elimination. In an additional step, for the study region with the higher pig density (2463 pigs/km(2) farmland), the potential distribution of PRRSV-free and non-free herds during the implementation of a national control program aiming at national virus elimination was modeled. Complex herd and trade network structures suggest that PRRSV elimination in regions with intensive pig farming like that of middle Europe would have to involve legal regulation and be accompanied by important trade and animal movement restrictions. The proposed methodology of risk index mapping could be adapted to areas varying in size, herd structure and density. Interpreted in the regional context, this could help to classify the density of risk and to accordingly target resources and measures for elimination.

Assessment of expected damage on buildings subjected to Lorca earthquake through an energy-based seismic index method and nonlinear dynamic response analyses

The city of Lorca (Spain) was hit on May 11th, 2011, by two consecutive earth-quakes of magnitudes 4.6 and 5.2 Mw, causing casualties and important damage in buildings. Many of the damaged structures were reinforced concrete frames with wide beams. This study quantifies the expected level of damage on this structural type in the case of the Lorca earth-quake by means of a seismic index Iv that compares the energy input by the earthquake with the energy absorption/dissipation capacity of the structure. The prototype frames investigated represent structures designed in two time periods (1994–2002 and 2003–2008), in which the applicable codes were different. The influence of the masonry infill walls and the proneness of the frames to concentrate damage in a given story were further investigated through nonlinear dynamic response analyses. It is found that (1) the seismic index method predicts levels of damage that range from moderate/severe to complete collapse; this prediction is consistent with the observed damage; (2) the presence of masonry infill walls makes the structure very prone to damage concentration and reduces the overall seismic capacity of the building; and (3) a proper hierarchy of strength between beams and columns that guarantees the formation of a strong column-weak beam mechanism (as prescribed by seismic codes), as well as the adoption of counter-measures to avoid the negative interaction between non-structural infill walls and the main frame, would have reduced the level of damage from Iv=1 (collapse) to about Iv=0.5 (moderate/severe damage)