Smoothed histogram modification for image processing

The technique of constructing a transformation, or regrading, of a discrete data set such that the histogram of the transformed data matches a given reference histogram is commonly known as histogram modification. The technique is widely used for image enhancement and normalization. A method which has been previously derived for producing such a regrading is shown to be “best” in the sense that it minimizes the error between the cumulative histogram of the transformed data and that of the given reference function, over all single-valued, monotone, discrete transformations of the data. Techniques for smoothed regrading, which provide a means of balancing the error in matching a given reference histogram against the information lost with respect to a linear transformation are also examined. The smoothed regradings are shown to optimize certain cost functionals. Numerical algorithms for generating the smoothed regradings, which are simple and efficient to implement, are described, and practical applications to the processing of LANDSAT image data are discussed.

Phylogenetic variation in the tolerance and uptake of organic contaminants

An investigation into the phylogenetic variation of plant tolerance and the root and shoot uptake of organic contaminants was undertaken. The aim was to determine if particular families or genera were tolerant of, or accumulated organic pollutants. Data were collected from sixty-nine studies. The variation between experiments was accounted for using a residual maximum likelihood analysis to approximate means for individual taxa. A nested ANOVA was subsequently used to determine differences at a number of differing phylogenetic levels. Significant differences were observed at a number of phylogenetic levels for the tolerance to TPH, the root concentration factor and the shoot concentration factor. There was no correlation between the uptake of organic pollutants and that of heavy metals. The data indicate that plant phylogeny is an important influence on both the plant tolerance and uptake of organic pollutants. If this study can be expanded, such information can be used when designing plantings for phytoremediation or risk reduction during the restoration of contaminated sites.

Modelling habitat selection and distribution of the critically endangered Jerdon's courser Rhinoptilus bitorquatus in scrub jungle: an application of a new tracking method

1. Jerdon's courser Rhinoptilus bitorquatus is a nocturnally active cursorial bird that is only known to occur in a small area of scrub jungle in Andhra Pradesh, India, and is listed as critically endangered by the IUCN. Information on its habitat requirements is needed urgently to underpin conservation measures. We quantified the habitat features that correlated with the use of different areas of scrub jungle by Jerdon's coursers, and developed a model to map potentially suitable habitat over large areas from satellite imagery and facilitate the design of surveys of Jerdon's courser distribution. 2. We used 11 arrays of 5-m long tracking strips consisting of smoothed fine soil to detect the footprints of Jerdon's coursers, and measured tracking rates (tracking events per strip night). We counted the number of bushes and trees, and described other attributes of vegetation and substrate in a 10-m square plot centred on each strip. We obtained reflectance data from Landsat 7 satellite imagery for the pixel within which each strip lay. 3. We used logistic regression models to describe the relationship between tracking rate by Jerdon's coursers and characteristics of the habitat around the strips, using ground-based survey data and satellite imagery. 4. Jerdon's coursers were most likely to occur where the density of large (>2 m tall) bushes was in the range 300-700 ha(-1) and where the density of smaller bushes was less than 1000 ha(-1). This habitat was detectable using satellite imagery. 5. Synthesis and applications. The occurrence of Jerdon's courser is strongly correlated with the density of bushes and trees, and is in turn affected by grazing with domestic livestock, woodcutting and mechanical clearance of bushes to create pasture, orchards and farmland. It is likely that there is an optimal level of grazing and woodcutting that would maintain or create suitable conditions for the species. Knowledge of the species' distribution is incomplete and there is considerable pressure from human use of apparently suitable habitats. Hence, distribution mapping is a high conservation priority. A two-step procedure is proposed, involving the use of ground surveys of bush density to calibrate satellite image-based mapping of potential habitat. These maps could then be used to select priority areas for Jerdon's courser surveys. The use of tracking strips to study habitat selection and distribution has potential in studies of other scarce and secretive species.

Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data

This article explores how data envelopment analysis (DEA), along with a smoothed bootstrap method, can be used in applied analysis to obtain more reliable efficiency rankings for farms. The main focus is the smoothed homogeneous bootstrap procedure introduced by Simar and Wilson (1998) to implement statistical inference for the original efficiency point estimates. Two main model specifications, constant and variable returns to scale, are investigated along with various choices regarding data aggregation. The coefficient of separation (CoS), a statistic that indicates the degree of statistical differentiation within the sample, is used to demonstrate the findings. The CoS suggests a substantive dependency of the results on the methodology and assumptions employed. Accordingly, some observations are made on how to conduct DEA in order to get more reliable efficiency rankings, depending on the purpose for which they are to be used. In addition, attention is drawn to the ability of the SLICE MODEL, implemented in GAMS, to enable researchers to overcome the computational burdens of conducting DEA (with bootstrapping).

Response of a weed community to different management practice in field bean

Weed control strategies for field beans were studied in North-eastern Croatia. This study focused on how different weed management practices affect weed community composition. The recommended pre-emergence herbicide application was compared to different treatments of post-emergence herbicide (broadcasted or banded over crop rows) and mechanical weed control in order to explore the response of a weed community to different management practice. Weed density data were used to compare total community densities by weed management strategies and to calculate diversity indices (Shannon's H', Shannon's E and Margalef's D-MG). Data were analyzed using ANOVA and multivariate technique. Weed community structure was generally similar in the post-emergence herbicide treatments, which were dominated by a few species that had high relative abundance values, while most of the species were of lower abundance. Notable fluctuations in weed communities corresponded with variation in weather patterns and management practice.

Describing long-term trends in precipitation using generalized additive models

With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.

Mechanisms of inverse agonist action at D-2 dopamine receptors

1 Mechanisms of inverse agonist action at the D-2(short) dopamine receptor have been examined. 2 Discrimination of G-protein-coupled and -uncoupled forms of the receptor by inverse agonists was examined in competition ligand-binding studies versus the agonist [H-3]NPA at a concentration labelling both G-protein-coupled and -uncoupled receptors. 3 Competition of inverse agonists versus [H-3] NPA gave data that were fitted best by a two-binding site model in the absence of GTP but by a one-binding site model in the presence of GTP. K-i values were derived from the competition data for binding of the inverse agonists to G-protein-uncoupled and -coupled receptors. K-coupled and K-uncoupled were statistically different for the set of compounds tested ( ANOVA) but the individual values were different in a post hoc test only for (+)-butaclamol. 4 These observations were supported by simulations of these competition experiments according to the extended ternary complex model. 5 Inverse agonist efficacy of the ligands was assessed from their ability to reduce agonist-independent [S-35]GTPγ S binding to varying degrees in concentration-response curves. Inverse agonism by (+)-butaclamol and spiperone occurred at higher potency when GDP was added to assays, whereas the potency of (-)-sulpiride was unaffected. 6 These data show that some inverse agonists ((+)-butaclamol, spiperone) achieve inverse agonism by stabilising the uncoupled form of the receptor at the expense of the coupled form. For other compounds tested, we were unable to define the mechanism.

Modelling habitat selection and distribution of the critically endangered Jerdon's courser Rhinoptilus bitorquatus in scrub jungle: an application of a new tracking method

1. Jerdon's courser Rhinoptilus bitorquatus is a nocturnally active cursorial bird that is only known to occur in a small area of scrub jungle in Andhra Pradesh, India, and is listed as critically endangered by the IUCN. Information on its habitat requirements is needed urgently to underpin conservation measures. We quantified the habitat features that correlated with the use of different areas of scrub jungle by Jerdon's coursers, and developed a model to map potentially suitable habitat over large areas from satellite imagery and facilitate the design of surveys of Jerdon's courser distribution. 2. We used 11 arrays of 5-m long tracking strips consisting of smoothed fine soil to detect the footprints of Jerdon's coursers, and measured tracking rates (tracking events per strip night). We counted the number of bushes and trees, and described other attributes of vegetation and substrate in a 10-m square plot centred on each strip. We obtained reflectance data from Landsat 7 satellite imagery for the pixel within which each strip lay. 3. We used logistic regression models to describe the relationship between tracking rate by Jerdon's coursers and characteristics of the habitat around the strips, using ground-based survey data and satellite imagery. 4. Jerdon's coursers were most likely to occur where the density of large (>2 m tall) bushes was in the range 300-700 ha(-1) and where the density of smaller bushes was less than 1000 ha(-1). This habitat was detectable using satellite imagery. 5. Synthesis and applications. The occurrence of Jerdon's courser is strongly correlated with the density of bushes and trees, and is in turn affected by grazing with domestic livestock, woodcutting and mechanical clearance of bushes to create pasture, orchards and farmland. It is likely that there is an optimal level of grazing and woodcutting that would maintain or create suitable conditions for the species. Knowledge of the species' distribution is incomplete and there is considerable pressure from human use of apparently suitable habitats. Hence, distribution mapping is a high conservation priority. A two-step procedure is proposed, involving the use of ground surveys of bush density to calibrate satellite image-based mapping of potential habitat. These maps could then be used to select priority areas for Jerdon's courser surveys. The use of tracking strips to study habitat selection and distribution has potential in studies of other scarce and secretive species.

Expression profiles in the progression of ductal carcinoma in the breast

An understanding of the multi-step nature of cancer as it is in the breast, as a series of pivotal genetic/epigenetic modifications is irrefutably a milestone in diagnostics, prognostics and eventually providing a cure. Here we have utilised a variant of analysis of variance (ANOVA) as a model for the identification and tracking of specific mRNA species whose transcription has been significantly altered at each grade in the progression of ductal carcinoma, making it possible to correlate histological progression with the genetic events underlying breast cancer. We show that in the progression of ductal carcinomas, from grade 1 to 3, there is a reduction in the actual number of mRNA species, which are significantly over or under expressed. We also show that this technique can be employed to generate differential gene expression patterns, whereby the combined expression profile of the tailored spectra of genes in the comparison of each ductal grade is sufficient to render them on clearly separate arms of an array-wise hierarchical cluster dendrogram.

The impact of ICT on the work patterns of managers and their organisations

Purpose – The main aim of this paper is to present the results of a study examining managers' attitudes towards the deployment and use of information and communications technology (ICT) in their organisations. The study comes at a time when ICT is being recognised as a major enabler of innovation and new business models, which have the potential to have major impact on western economies and jobs. Design/methodology/approach – A questionnaire was specially designed to collect data relating to three research questions. The questionnaire also included a number of open-ended questions. A total of 181 managers from a wide range of industries across a number of countries participated in the electronic survey. The quantitative responses to the survey were analysed using SPSS. Exploratory factor analysis using Varimax rotation was used and ANOVA to compare responses by different groups. Findings – The survey showed that many of the respondents appeared equipped to work “any place, any time”. However, it also highlighted the challenges managers face in working in a connected operation. Also, the data suggested that many managers were less than confident about their companies' policies and practices in relation to information management. Originality/value – A next step from this exploratory research could be the development of a model exploring the impact of ICT on management and organisational performance in terms of personal characteristics of the manager, the role performed, the context and the ICT provision. Also, further research could focus on examining in more detail differences between management levels.

Mechanisms of inverse agonist action at D-2 dopamine receptors

1 Mechanisms of inverse agonist action at the D-2(short) dopamine receptor have been examined. 2 Discrimination of G-protein-coupled and -uncoupled forms of the receptor by inverse agonists was examined in competition ligand-binding studies versus the agonist [H-3]NPA at a concentration labelling both G-protein-coupled and -uncoupled receptors. 3 Competition of inverse agonists versus [H-3] NPA gave data that were fitted best by a two-binding site model in the absence of GTP but by a one-binding site model in the presence of GTP. K-i values were derived from the competition data for binding of the inverse agonists to G-protein-uncoupled and -coupled receptors. K-coupled and K-uncoupled were statistically different for the set of compounds tested ( ANOVA) but the individual values were different in a post hoc test only for (+)-butaclamol. 4 These observations were supported by simulations of these competition experiments according to the extended ternary complex model. 5 Inverse agonist efficacy of the ligands was assessed from their ability to reduce agonist-independent [S-35]GTPγ S binding to varying degrees in concentration-response curves. Inverse agonism by (+)-butaclamol and spiperone occurred at higher potency when GDP was added to assays, whereas the potency of (-)-sulpiride was unaffected. 6 These data show that some inverse agonists ((+)-butaclamol, spiperone) achieve inverse agonism by stabilising the uncoupled form of the receptor at the expense of the coupled form. For other compounds tested, we were unable to define the mechanism.

Modeling the effects of node heterogeneity on the performance of a real grid application

The performance benefit when using Grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effect of the synchronization overhead, mainly due to the high variability of completion times of the different tasks, which, in turn, is due to the large heterogeneity of Grid nodes. For this reason, it is important to have models which capture the performance of such systems. In this paper we describe a queueing-network-based performance model able to accurately analyze Grid architectures, and we use the model to study a real parallel application executed in a Grid. The proposed model improves the classical modelling techniques and highlights the impact of resource heterogeneity and network latency on the application performance.

Modeling the effects of node heterogeneity on the performance of grid applications

The performance benefit when using grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effects of synchronization overheads, mainly due to the high variability in the execution times of the different tasks, which, in turn, is accentuated by the large heterogeneity of grid nodes. In this paper we design hierarchical, queuing network performance models able to accurately analyze grid architectures and applications. Thanks to the model results, we introduce a new allocation policy based on a combination between task partitioning and task replication. The models are used to study two real applications and to evaluate the performance benefits obtained with allocation policies based on task replication.