Pattern of attack of a galling insect reveals an unexpected preference-performance linkage on medium-sized resources

Pattern of attack of a galling insect reveals an unexpected preference-performance linkage on medium-sized resources. The Plant Vigor Hypothesis (PVH) predicts oviposition preference and higher offspring performance on longer and fast-growing shoots, and although several studies have tested its predictions, long-term studies concerning the patterns of host selection by galling species are still lacking. The PVH was tested in this study using Bauhinia brevipes (Fabaceae) as the host of a leaf gall midge, Asphondylia microcapillata (Diptera, Cecidomyiidae) during three consecutive years. Shoots were collected from the same 80 plants between 2001 and 2003 and shoot length, number of healthy and galled leaves, gall number, and mortality factors were recorded. Nearly 600 galls were found on the 5,800 shoots collected. Medium-sized shoots supported from 46 to 70% of all galls, with greater gall survival rate in 2002 and 2003. A decrease in parasitism rate coupled with an increase in gall predation lead to a constant similar gall survivorship rate in all years (x = 22.7%). Although gall abundance varied among years (122 in 2001, 114 in 2002 and 359 in 2003) preference for longer shoots was not observed because the percentage of galled shoots and galled leaves were higher on medium shoot length classes in all years. The observed distribution of gall abundance and galled shoots were always greater than the expected distribution on medium shoot length classes. These findings do not support the PVH, and show that A. microcapillata can maximize the female preference and larval performance on medium-sized shoots of B. brevipes.

Calibration of high-resolution geophysical data with tracer test measurements to improve hydrological predictions

Relationships between porosity and hydraulic conductivity tend to be strongly scale- and site-dependent and are thus very difficult to establish. As a result, hydraulic conductivity distributions inferred from geophysically derived porosity models must be calibrated using some measurement of aquifer response. This type of calibration is potentially very valuable as it may allow for transport predictions within the considered hydrological unit at locations where only geophysical measurements are available, thus reducing the number of well tests required and thereby the costs of management and remediation. Here, we explore this concept through a series of numerical experiments. Considering the case of porosity characterization in saturated heterogeneous aquifers using crosshole ground-penetrating radar and borehole porosity log data, we use tracer test measurements to calibrate a relationship between porosity and hydraulic conductivity that allows the best prediction of the observed hydrological behavior. To examine the validity and effectiveness of the obtained relationship, we examine its performance at alternate locations not used in the calibration procedure. Our results indicate that this methodology allows us to obtain remarkably reliable hydrological predictions throughout the considered hydrological unit based on the geophysical data only. This was also found to be the case when significant uncertainty was considered in the underlying relationship between porosity and hydraulic conductivity.

MEPDG Work Plan Task No. 8: Validation of Pavement Performance Curves for the Mechanistic-Empirical Pavement Design Guide, 2009

The objective of this research is to determine whether the nationally calibrated performance models used in the Mechanistic-Empirical Pavement Design Guide (MEPDG) provide a reasonable prediction of actual field performance, and if the desired accuracy or correspondence exists between predicted and monitored performance for Iowa conditions. A comprehensive literature review was conducted to identify the MEPDG input parameters and the MEPDG verification/calibration process. Sensitivities of MEPDG input parameters to predictions were studied using different versions of the MEPDG software. Based on literature review and sensitivity analysis, a detailed verification procedure was developed. A total of sixteen different types of pavement sections across Iowa, not used for national calibration in NCHRP 1-47A, were selected. A database of MEPDG inputs and the actual pavement performance measures for the selected pavement sites were prepared for verification. The accuracy of the MEPDG performance models for Iowa conditions was statistically evaluated. The verification testing showed promising results in terms of MEPDG’s performance prediction accuracy for Iowa conditions. Recalibrating the MEPDG performance models for Iowa conditions is recommended to improve the accuracy of predictions. ****************** Large File**************************

Improving the Accuracy of Camber Predictions for Precast Pretensioned Concrete Beams, TR-625, 2015

The discrepancies between the designed and measured camber of precast pretensioned concrete beams (PPCBs) observed by the Iowa DOT have created challenges in the field during bridge construction, causing construction delays and additional costs. This study was undertaken to systematically identify the potential sources of discrepancies between the designed and measured camber from release to time of erection and improve the accuracy of camber estimations in order to minimize the associated problems in the field. To successfully accomplish the project objectives, engineering properties, including creep and shrinkage, of three normal concrete and four high-performance concrete mix designs were characterized. In parallel, another task focused on identifying the instantaneous camber and the variables affecting the instantaneous camber and evaluated the corresponding impact of this factor using more than 100 PPCBs. Using a combination of finite element analyses and the time-step method, the long-term camber was estimated for 66 PPCBs, with due consideration given to creep and shrinkage of concrete, changes in support location and prestress force, and the thermal effects. Utilizing the outcomes of the project, suitable long-term camber multipliers were developed that account for the time-dependent behavior, including the thermal effects. It is shown that by using the recommended practice for the camber measurements together with the proposed multipliers, the accuracy of camber prediction will be greatly improved. Consequently, it is expected that future bridge projects in Iowa can minimize construction challenges resulting from large discrepancies between the designed and actual camber of PPCBs during construction.

A Continuous Span Aluminum Girder Concrete Deck Bridge - Part 1 of 2: Field Test Performance and Evaluation, 1996

This report addresses the field testing and analysis of those results to establish the behavior of the original Clive Road Bridge that carried highway traffic over Interstate 80 (I-80) in the northwest region of Des Moines, Iowa. The bridge was load tested in 1959, shortly after its construction and in 1993, just prior to its demolition. This report presents some of the results from both field tests, finite element predictions of the behavior of aluminum bridge girders, and load distribution studies.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Stability of cognitive performance in children with mild intellectual disability.

AIM: Longitudinal studies that have examined cognitive performance in children with intellectual disability more than twice over the course of their development are scarce. We assessed population and individual stability of cognitive performance in a clinical sample of children with borderline to mild non-syndromic intellectual disability. METHOD: Thirty-six children (28 males, eight females; age range 3-19y) with borderline to mild intellectual disability (Full-scale IQ [FSIQ] 50-85) of unknown origin were examined in a retrospective clinical case series using linear mixed models including at least three assessments with standardized intelligence tests. RESULTS: Average cognitive performance remained remarkably stable over time (high population stability, drop of only 0.38 IQ points per year, standard error=0.39, p=0.325) whereas individual stability was at best moderate (intraclass correlation of 0.58), indicating that about 60% of the residual variation in FSIQ scores can be attributed to between-child variability. Neither sex nor socio-economic status had a statistically significant impact on FSIQ. INTERPRETATION: Although intellectual disability during childhood is a relatively stable phenomenon, individual stability of IQ is only moderate, likely to be caused by test-to-test reliability (e.g. level of child's cooperation, motivation, and attention). Therefore, clinical decisions and predictions should not rely on single IQ assessments, but should also consider adaptive functioning and previous developmental history.

Task complexity, the Cognition Hypothesis and second language learning and performance

In this paper we describe a taxonomy of task demands which distinguishes between Task Complexity, Task Condition and Task Difficulty. We then describe three theoretical claims and predictions of the Cognition Hypothesis (Robinson 2001, 2003b, 2005a) concerning the effects of task complexity on: (a) language production; (b) interaction and uptake of information available in the input to tasks; and (c) individual differences-task interactions. Finally we summarize the findings of the empirical studies in this special issue which all address one or more of these predictions and point to some directions for continuing, future research into the effects of task complexity on learning and performance.

On performance persistence in emerging markets: Empirical evidence from Asia-Pacific

The purpose of this study is to investigate the performance persistence of international mutual funds, employing a data sample which includes 2,168 European mutual funds investing in Asia-Pacific region; Japan excluded. Also, a number of performance measures is tested and compared, and especially, this study tries to find out whether iterative Bayesian procedure can be used to provide more accurate predictions on future performance. Finally, this study examines whether the cross-section of mutual fund returns can be explained with simple accounting variables and market risk. To exclude the effect of the Asian currency crisis in 1997, the studied time period includes years from 1999 to 2007. The overall results showed significant performance persistence for repeating winners when performance was tested with contingency tables. Also the annualized alpha spreads between the top and bottom portfolios were more than ten percent at their highest. Nevertheless, the results do not confirm the improved prediction accuracy of the Bayesian alphas.

Predicting performance on fluid intelligence from speed of processing, working memory, and controlled attention

Fluid inteliigence has been defined as an innate ability to reason which is measured commonly by the Raven's Progressive Matrices (RPM). Individual differences in fluid intelligence are currently explained by the Cascade model (Fry & Hale, 1996) and the Controlled Attention hypothesis (Engle, Kane, & Tuholski, 1999; Kane & Engle, 2002). The first theory is based on a complex relation among age, speed, and working memory which is described as a Cascade. The alternative to this theory, the Controlled Attention hypothesis, is based on the proposition that it is the executive attention component of working memory that explains performance on fluid intelligence tests. The first goal of this study was to examine whether the Cascade model is consistent within the visuo-spatial and verbal-numerical modalities. The second goal was to examine whether the executive attention component ofworking memory accounts for the relation between working memory and fluid intelligence. Two hundred and six undergraduate students between the ages of 18 and 28 completed a battery of cognitive tests selected to measure processing speed, working memory, and controlled attention which were selected from two cognitive modalities, verbalnumerical and visuo-spatial. These were used to predict performance on two standard measures of fluid intelligence: the Raven's Progressive Matrices (RPM) and the Shipley Institute of Living Scales (SILS) subtests. Multiple regression and Structural Equation Modeling (SEM) were used to test the Cascade model and to determine the independent and joint effects of controlled attention and working memory on general fluid intelligence. Among the processing speed measures only spatial scan was related to the RPM. No other significant relations were observed between processing speed and fluid intelligence. As 1 a construct, working memory was related to the fluid intelligence tests. Consistent with the predictions for the RPM there was support for the Cascade model within the visuo-spatial modality but not within the verbal-numerical modality. There was no support for the Cascade model with respect to the SILS tests. SEM revealed that there was a direct path between controlled attention and RPM and between working memory and RPM. However, a significant path between set switching and RPM explained the relation between controlled attention and RPM. The prediction that controlled attention mediated the relation between working memory and RPM was therefore not supported. The findings support the view that the Cascade model may not adequately explain individual differences in fluid intelligence and this may be due to the differential relations observed between working memory and fluid intelligence across different modalities. The findings also show that working memory is not a domain-general construct and as a result its relation with fluid intelligence may be dependent on the nature of the working memory modality.

Redundancy gain : manifestations, causes and predictions

Les temps de réponse dans une tache de reconnaissance d’objets visuels diminuent de façon significative lorsque les cibles peuvent être distinguées à partir de deux attributs redondants. Le gain de redondance pour deux attributs est un résultat commun dans la littérature, mais un gain causé par trois attributs redondants n’a été observé que lorsque ces trois attributs venaient de trois modalités différentes (tactile, auditive et visuelle). La présente étude démontre que le gain de redondance pour trois attributs de la même modalité est effectivement possible. Elle inclut aussi une investigation plus détaillée des caractéristiques du gain de redondance. Celles-ci incluent, outre la diminution des temps de réponse, une diminution des temps de réponses minimaux particulièrement et une augmentation de la symétrie de la distribution des temps de réponse. Cette étude présente des indices que ni les modèles de course, ni les modèles de coactivation ne sont en mesure d’expliquer l’ensemble des caractéristiques du gain de redondance. Dans ce contexte, nous introduisons une nouvelle méthode pour évaluer le triple gain de redondance basée sur la performance des cibles doublement redondantes. Le modèle de cascade est présenté afin d’expliquer les résultats de cette étude. Ce modèle comporte plusieurs voies de traitement qui sont déclenchées par une cascade d’activations avant de satisfaire un seul critère de décision. Il offre une approche homogène aux recherches antérieures sur le gain de redondance. L’analyse des caractéristiques des distributions de temps de réponse, soit leur moyenne, leur symétrie, leur décalage ou leur étendue, est un outil essentiel pour cette étude. Il était important de trouver un test statistique capable de refléter les différences au niveau de toutes ces caractéristiques. Nous abordons la problématique d’analyser les temps de réponse sans perte d’information, ainsi que l’insuffisance des méthodes d’analyse communes dans ce contexte, comme grouper les temps de réponses de plusieurs participants (e. g. Vincentizing). Les tests de distributions, le plus connu étant le test de Kolmogorov- Smirnoff, constituent une meilleure alternative pour comparer des distributions, celles des temps de réponse en particulier. Un test encore inconnu en psychologie est introduit : le test d’Anderson-Darling à deux échantillons. Les deux tests sont comparés, et puis nous présentons des indices concluants démontrant la puissance du test d’Anderson-Darling : en comparant des distributions qui varient seulement au niveau de (1) leur décalage, (2) leur étendue, (3) leur symétrie, ou (4) leurs extrémités, nous pouvons affirmer que le test d’Anderson-Darling reconnait mieux les différences. De plus, le test d’Anderson-Darling a un taux d’erreur de type I qui correspond exactement à l’alpha tandis que le test de Kolmogorov-Smirnoff est trop conservateur. En conséquence, le test d’Anderson-Darling nécessite moins de données pour atteindre une puissance statistique suffisante.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

Comparison of predictions of baking volume using large deformation rheological properties

Three large deformation rheological tests, the Kieffer dough extensibility system, the D/R dough inflation system and the 2 g mixograph test, were carried out on doughs made from a large number of winter wheat lines and cultivars grown in Poland. These lines and cultivars represented a broad spread in baking performance in order to assess their suitability as predictors of baking volume. The parameters most closely associated with baking volume were strain hardening index, bubble failure strain, and mixograph bandwidth at 10min. Simple correlations with baking volume indicate that bubble failure strain and strain hardening index give the highest correlations, whilst the use of best subsets regression, which selects the best combination of parameters, gave increased correlations with R-2 = 0.865 for dough inflation parameters, R-2 = 0. 842 for Kieffer parameters and R-2 = 0.760 for mixograph parameters. (c) 2007 Elsevier Ltd. All rights reserved.

Predicting the annual performance of UK real estate: timeliness versus coverage

The IPD Annual Index is the largest and most comprehensive Real Estate market index available in the UK Such coverage however inevitably leads to delays in publication. In contrast there are a number of quarterly and monthly indices which are published within days of the year end but which lack the coverage in terms of size and numbers of properties. This paper analyses these smaller but more timely indices to see whether such indices can be used to predict the performance of the IPD Annual Index. Using a number of measures of forecasting accuracy it is shown that the smaller indices provide unbiased and efficient predictions of the IPD Annual Index. Such indices also significantly outperform a naive no-change model. Although no one index performs significantly better than the others. The more timely indices however do not perfectly track the IPD Annual Index. As a result any short run predictions of performance will be subject to a degree of error. Nevertheless the more timely indices, although lacking authoritative coverage, provide a valuable service to investors giving good estimates of Real Estates performance well before the publication of the IPD Annual Index.

Elevated atmospheric carbon dioxide impairs the performance of root-feeding vine weevils by modifying root growth and secondary metabolites

Predicting how insect crop pests will respond to global climate change is an important part of increasing crop production for future food security, and will increasingly rely on empirically based evidence. The effects of atmospheric composition, especially elevated carbon dioxide (eCO(2)), on insect herbivores have been well studied, but this research has focussed almost exclusively on aboveground insects. However, responses of root-feeding insects to eCO(2) are unlikely to mirror these trends because of fundamental differences between aboveground and belowground habitats. Moreover, changes in secondary metabolites and defensive responses to insect attack under eCO(2) conditions are largely unexplored for root herbivore interactions. This study investigated how eCO(2) (700 mu mol mol-1) affected a root-feeding herbivore via changes to plant growth and concentrations of carbon (C), nitrogen (N) and phenolics. This study used the root-feeding vine weevil, Otiorhynchus sulcatus and the perennial crop, Ribes nigrum. Weevil populations decreased by 33% and body mass decreased by 23% (from 7.2 to 5.4 mg) in eCO(2). Root biomass decreased by 16% in eCO(2), which was strongly correlated with weevil performance. While root N concentrations fell by 8%, there were no significant effects of eCO(2) on root C and N concentrations. Weevils caused a sink in plants, resulting in 8-12% decreases in leaf C concentration following herbivory. There was an interactive effect of CO(2) and root herbivory on root phenolic concentrations, whereby weevils induced an increase at ambient CO(2), suggestive of defensive response, but caused a decrease under eCO(2). Contrary to predictions, there was a positive relationship between root phenolics and weevil performance. We conclude that impaired root-growth underpinned the negative effects of eCO(2) on vine weevils and speculate that the plant's failure to mount a defensive response at eCO(2) may have intensified these negative effects.