Survival analysis statistics applied to threshold data obtained from the ascending forced-choice method of limits

Sensory thresholds are often collected through ascending forced-choice methods. Group thresholds are important for comparing stimuli or populations; yet, the method has two problems. An individual may correctly guess the correct answer at any concentration step and might detect correctly at low concentrations but become adapted or fatigued at higher concentrations. The survival analysis method deals with both issues. Individual sequences of incorrect and correct answers are adjusted, taking into account the group performance at each concentration. The technique reduces the chance probability where there are consecutive correct answers. Adjusted sequences are submitted to survival analysis to determine group thresholds. The technique was applied to an aroma threshold and a taste threshold study. It resulted in group thresholds similar to ASTM or logarithmic regression procedures. Significant differences in taste thresholds between younger and older adults were determined. The approach provides a more robust technique over previous estimation methods.

Parental death as a vital conjuncture? Intergenerational care and responsibility following bereavement in Senegal

This article explores the ways that parental death represents a 'vital conjuncture' for Serer young people that reconfigures and potentially transforms intergenerational caring responsibilities in different spatial and temporal contexts. Drawing on semi-structured interviews with young people (aged 15-27), family members, religious and community leaders and professionals in rural and urban Senegal, I explore young people's responses to parental death. 'Continuing bonds' with the deceased were expressed through memories evoked in homespace, shared family practices and gendered responsibilities to 'take care of' bereaved family members, to cultivate inherited farmland and to fulfil the wishes of the deceased. Parental death could reconfigure intergenerational care and lead to shifts in power dynamics, as eldest sons asserted their position of authority. While care-giving roles were associated with agency, the low social status accorded to young women's paid and unpaid domestic work undermined their efforts. The research contributes to understandings of gendered nuances in the experience of bereavement and continuing bonds and provides insight into intra-household decision-making processes, ownership and control of assets. Analysis of the culturally specific meanings of relationships and a young person's social location within hierarchies of gender, age, sibling birth order and wider socio-cultural norms and practices is needed.

Estimating correlated observation error statistics using an ensemble transform Kalman filter

For certain observing types, such as those that are remotely sensed, the observation errors are correlated and these correlations are state- and time-dependent. In this work, we develop a method for diagnosing and incorporating spatially correlated and time-dependent observation error in an ensemble data assimilation system. The method combines an ensemble transform Kalman filter with a method that uses statistical averages of background and analysis innovations to provide an estimate of the observation error covariance matrix. To evaluate the performance of the method, we perform identical twin experiments using the Lorenz ’96 and Kuramoto-Sivashinsky models. Using our approach, a good approximation to the true observation error covariance can be recovered in cases where the initial estimate of the error covariance is incorrect. Spatial observation error covariances where the length scale of the true covariance changes slowly in time can also be captured. We find that using the estimated correlated observation error in the assimilation improves the analysis.

Using reanalysis data to quantify extreme wind power generation statistics : a 33 year case study in Great Britain

With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

Theoretical insight into diagnosing observation error correlations using observation-minus-background and observation-minus-analysis statistics

To improve the quantity and impact of observations used in data assimilation it is necessary to take into account the full, potentially correlated, observation error statistics. A number of methods for estimating correlated observation errors exist, but a popular method is a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. The accuracy of the results it yields is unknown as the diagnostic is sensitive to the difference between the exact background and exact observation error covariances and those that are chosen for use within the assimilation. It has often been stated in the literature that the results using this diagnostic are only valid when the background and observation error correlation length scales are well separated. Here we develop new theory relating to the diagnostic. For observations on a 1D periodic domain we are able to the show the effect of changes in the assumed error statistics used in the assimilation on the estimated observation error covariance matrix. We also provide bounds for the estimated observation error variance and eigenvalues of the estimated observation error correlation matrix. We demonstrate that it is still possible to obtain useful results from the diagnostic when the background and observation error length scales are similar. In general, our results suggest that when correlated observation errors are treated as uncorrelated in the assimilation, the diagnostic will underestimate the correlation length scale. We support our theoretical results with simple illustrative examples. These results have potential use for interpreting the derived covariances estimated using an operational system.

A new calibrated sunspot group series since 1749: statistics of active day fractions

Although the sunspot-number series have existed since the mid-19th century, they are still the subject of intense debate, with the largest uncertainty being related to the "calibration" of the visual acuity of individual observers in the past. Daisy-chain regression methods are applied to inter-calibrate the observers which may lead to significant bias and error accumulation. Here we present a novel method to calibrate the visual acuity of the key observers to the reference data set of Royal Greenwich Observatory sunspot groups for the period 1900-1976, using the statistics of the active-day fraction. For each observer we independently evaluate their observational thresholds [S_S] defined such that the observer is assumed to miss all of the groups with an area smaller than S_S and report all the groups larger than S_S. Next, using a Monte-Carlo method we construct, from the reference data set, a correction matrix for each observer. The correction matrices are significantly non-linear and cannot be approximated by a linear regression or proportionality. We emphasize that corrections based on a linear proportionality between annually averaged data lead to serious biases and distortions of the data. The correction matrices are applied to the original sunspot group records for each day, and finally the composite corrected series is produced for the period since 1748. The corrected series displays secular minima around 1800 (Dalton minimum) and 1900 (Gleissberg minimum), as well as the Modern grand maximum of activity in the second half of the 20th century. The uniqueness of the grand maximum is confirmed for the last 250 years. It is shown that the adoption of a linear relationship between the data of Wolf and Wolfer results in grossly inflated group numbers in the 18th and 19th centuries in some reconstructions.

Diagnosing observation error correlations for Doppler radar radial winds in the Met Office UKV model using observation-minus-background and observation-minus-analysis statistics

With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.

Environmental controls on the distribution and diversity of lentic Chironomidae (Insecta: Diptera) across an altitudinal gradient in tropical South America

To predict the response of aquatic ecosystems to future global climate change, data on the ecology and distribution of keystone groups in freshwater ecosystems are needed. In contrast to mid- and high-latitude zones, such data are scarce across tropical South America (Neotropics). We present the distribution and diversity of chironomid species using surface sediments of 59 lakes from the Andes to the Amazon (0.1–17°S and 64–78°W) within the Neotropics. We assess the spatial variation in community assemblages and identify the key variables influencing the distributional patterns. The relationships between environmental variables (pH, conductivity, depth, and sediment organic content), climatic data, and chironomid assemblages were assessed using multivariate statistics (detrended correspondence analysis and canonical correspondence analysis). Climatic parameters (temperature and precipitation) were most significant in describing the variance in chironomid assemblages. Temperature and precipitation are both predicted to change under future climate change scenarios in the tropical Andes. Our findings suggest taxa of Orthocladiinae, which show a preference to cold high-elevation oligotrophic lakes, will likely see range contraction under future anthropogenic-induced climate change. Taxa abundant in areas of high precipitation, such as Micropsectra and Phaenopsectra, will likely become restricted to the inner tropical Andes, as the outer tropical Andes become drier. The sensitivity of chironomids to climate parameters makes them important bio-indicators of regional climate change in the Neotropics. Furthermore, the distribution of chironomid taxa presented here is a vital first step toward providing urgently needed autecological data for interpreting fossil chironomid records of past ecological and climate change from the tropical Andes.

SEM Study of Apical Morphological Alterations in Primary Teeth with Vital and Necrotic Pulps

This study evaluated, by SEM, the morphology of human primary teeth roots. Twenty-four teeth were divided into 3 groups: pulp vitality (group I) and pulp necrosis without (group II) and with apical periodontitis (group III). Roots were analyzed by the presence of periodontal ligament (PDL) fibers and resorption areas. In groups I and II, presence of PDL fibers and absence of resorption were observed in all cases (100%), while all specimens (100%) of group III showed no PDL fibers and resorption areas. In conclusion, there are morphological differences in the apical region of primary teeth with different pulpal and periapical pathologies.

Biofilm on the apical region of roots in primary teeth with vital and necrotic pulps with or without radiographically evident apical pathosis

Aim To evaluate, by scanning electron microscopy (SEM), the presence of biofilms on the external surfaces of the apical third of roots of human primary teeth with vital or necrotic pulps with and without radiographically evident periradicular pathosis. Methodology Eighteen teeth were selected: group I - normal pulp (n = 5), group II - pulp necrosis without radiographic evidence of periapical pathosis (n = 7) and group III - pulp necrosis with well-defined radiographic periapical pathosis (n = 6). After extraction, the teeth were washed with saline and immersed in 0.03 g mL(-1) trypsin solution for 20 min. The teeth were then washed in sodium cacodilate buffer and stored in receptacles containing modified Karnovsky solution. The teeth were sectioned, dehydrated in an ethanol series, critical-point dried with CO(2), sputter coated with gold and the external root surface in the apical third examined by SEM. Results In the teeth of groups I and II, the apical root surfaces were covered by collagen fibres, with no evidence of bacteria (100%). In the teeth of group III, the root apices had no collagen fibres but revealed resorptive areas containing microorganisms (cocci, bacilli, filaments and spirochetes) in all cases (100%). Conclusion Microorganisms organized as biofilms on the external root surface (extraradicular infection) were detected in primary teeth with pulp necrosis and radiographically visible periapical pathosis.

Conservative force fields in non-Gaussian statistics

In this Letter, we determine the kappa-distribution function for a gas in the presence of an external field of force described by a potential U(r). In the case of a dilute gas, we show that the kappa-power law distribution including the potential energy factor term can rigorously be deduced in the framework of kinetic theory with basis on the Vlasov equation. Such a result is significant as a preliminary to the discussion on the role of long range interactions in the Kaniadakis thermostatistics and the underlying kinetic theory. (C) 2008 Elsevier B.V. All rights reserved.

Metallopeptidase inhibitors arrest vital biological processes in the fungal pathogen Scedosporium apiospermum

P>Scedosporium apiospermum is an emerging agent of opportunistic mycoses in humans. Previously, we showed that mycelia of S. apiospermum secreted metallopeptidases which were directly linked to the destruction of key host proteins. In this study, we analysed the effect of metallopeptidase inhibitors on S. apiospermum development. As germination of inhaled conidia is a crucial event in the infectious process of S. apiospermum, we studied the morphological transformation induced by the incubation of conidia in Sabouraud-dextrose medium at 37 degrees C. After 6 h, some conidia presented a small projection resembling a germ-tube. A significant increase, around sixfold, in the germ-tube length was found after 12 h, and hyphae were exclusively observed after 24 h. Three distinct metallopeptidase inhibitors were able to arrest the transformation of conidia into hyphae in different ways; for instance, 1,10-phenanthroline (PHEN) completely blocked this process at 10 mu mol l-1, while ethylenediamine tetraacetic acid (EDTA) and ethylene glycol-bis (beta-aminoethyl ether; EGTA) only partially inhibited the differentiation at up to 10 mmol l-1. EGTA did not promote any significant reduction in the conidial growth, while PHEN and EDTA, both at 10 mmol l-1, inhibited the proliferation around 100% and 65%, respectively. The secretion of polypeptides into the extracellular environment and the metallopeptidase activity secreted by mycelia were completely inhibited by PHEN. These findings suggest that metallo-type enzymes could be potential targets for future therapeutic interventions against S. apiospermum.