Are the spatial patterns of weeds scale-invariant?

In previous empirical and modelling studies of rare species and weeds, evidence of fractal behaviour has been found. We propose that weeds in modern agricultural systems may be managed close to critical population dynamic thresholds, below which their rates of increase will be negative and where scale-invariance may be expected as a consequence. We collected detailed spatial data on five contrasting species over a period of three years in a primarily arable field. Counts in 20×20 cm contiguous quadrats, 225,000 in 1998 and 84,375 thereafter, could be re-structured into a wide range of larger quadrat sizes. These were analysed using three methods based on correlation sum, incidence and conditional incidence. We found non-trivial scale invariance for species occurring at low mean densities and where they were strongly aggregated. The fact that the scale-invariance was not found for widespread species occurring at higher densities suggests that the scaling in agricultural weed populations may, indeed, be related to critical phenomena.

Assessing reading at Key Stage 2: SATs as measures of children's inferential abilities

This article describes two studies. The first study was designed to investigate the ways in which the statutory assessments of reading for 11-year-old children in England assess inferential abilities. The second study was designed to investigate the levels of performance achieved in these tests in 2001 and 2002 by 11-year-old children attending state-funded local authority schools in one London borough. In the first study, content and questions used in the reading papers for the Standard Assessment Tasks (SATs) in the years 2001 and 2002 were analysed to see what types of inference were being assessed. This analysis suggested that the complexity involved in inference making and the variety of inference types that are made during the reading process are not adequately sampled in the SATs. Similar inadequacies are evident in the ways in which the programmes of study for literacy recommended by central government deal with inference. In the second study, scripts of completed SATs reading papers for 2001 and 2002 were analysed to investigate the levels of inferential ability evident in scripts of children achieving different SATs levels. The analysis in this article suggests that children who only just achieve the 'target' Level 4 do so with minimal use of inference skills. They are particularly weak in making inferences that require the application of background knowledge. Thus, many children who achieve the reading level (Level 4) expected of 11-year-olds are entering secondary education with insecure inference-making skills that have not been recognised.

Relation between the fatty acid composition of peripheral blood mononuclear cells and measures of immune cell function in health free-living subjects aged 25-72 y

Background: There is little information about the relation between the fatty acid composition of human immune cells and the function of those cells over the habitual range of fatty acid intakes. Objective: The objective of the study was to determine the relation between the fatty acid composition of human peripheral blood mononuclear cell (PBMC) phospholipids and the functions of human immune cells. Design: One hundred fifty healthy adult subjects provided a fasting blood sample. The phagocytic and oxidative burst activities of monocytes and neutrophils were measured in whole blood. PBMCs were isolated and used to measure lymphocyte proliferation in response to the T cell mitogen concanavalin A and the production of cytokines in response to concanavalin A or bacterial lipopolysaccharide. The fatty acid composition of plasma and PBMC phospholipids was determined. Results: Wide variations in fatty acid composition of PBMC phospholipids and immune cell functions were identified among the subjects. The proportions of total Polyunsaturated fatty acids (PUFAs), of total n-6 and n-3 PUFAs, and of several individual PUFAs in PBMC phospholipids were positively correlated with phagocytosis by neutrophils and monocytes, neutrophil oxidative burst, lymphocyte proliferation, and interferon gamma production. The ratios of saturated fatty acids to PUFAs and of n-6 to n-3 PUFAs were negatively correlated with these same immune functions. The relation of PBMC fatty acid composition to monocyte oxidative burst was the reverse of its relation to monocyte phagocytosis and neutrophil oxidative burst. Conclusion: Variations in the fatty acid composition of PBMC phospholipids account for some of the variability in immune cell functions among healthy adults.

Impact of menstrual cycle phase on insulin sensitivity measures and fasting lipids

There is evidence to suggest that insulin sensitivity may vary in response to changes in sex hormone levels. However, the results Of human studies designed to investigate changes in insulin sensitivity through the menstrual cycle have proved inconclusive. The aims of this Study were to 1) evaluate the impact of menstrual cycle phase on insulin sensitivity measures and 2) determine the variability Of insulin sensitivity measures within the same menstrual cycle phase. A controlled observational study of 13 healthy premenopausal women, not taking any hormone preparation and having regular menstrual cycles, was conducted. Insulin sensitivity (Si) and glucose effectiveness (Sg) were measured using an intravenous glucose tolerance test (IVGTT) with minimal model analysis. Additional Surrogate measures Of insulin sensitivity were calculated (homoeostasis model for insulin resistance [HOMA IR], quantitative insulin-to-glucose check index [QUICKI] and revised QUICKI [rQUICKI]), as well as plasma lipids. Each woman was tested in the luteal and follicular phases of her Menstrual cycle, and duplicate measures were taken in one phase of the cycle. No significant differences in insulin sensitivity (measured by the IVGTT or Surrogate markers) or plasma lipids were reported between the two phases of the menstrual cycle or between duplicate measures within the same phase. It was Concluded that variability in measures of insulin sensitivity were similar within and between menstrual phases.

Self-, parent-report and interview measures of obsessive-compulsive disorder in children and adolescents

Self-report measures of obsessive-compulsive disorder (OCD) in children and adolescents are needed for practical evaluation of severity and treatment response. We compared the self- and parent-report Obsessional Compulsive Inventory Revised (CHOCI-R) to the interview-based Child Yale-Brown Obsessive-Compulsive Scale (CY-BOCS) in a clinical sample of 285 children and adolescents with OCD. Classical test theory and item-response theory were applied to compare the instruments. The self- and parent-report CHOCI-R had good internal consistency and were strongly related to each other. The self- and parent-report CHOCI-R severity scores correlated with the CY-BOCS (Pearson's r 0.55 and 0.45 respectively). The CY-BOCS discriminated better at the severe end of the spectrum. The CHOCI-R provided better discrimination in the mild to moderate range. The time-efficient self- and parent-report alternatives will enable routine measurement of OCD severity in clinical practice. Estimates of equivalent summed scores are provided to facilitate comparison. (c) 2007 Elsevier Ltd. All rights reserved.

Analysis of the Fugl-Meyer outcome measures assessing the effectiveness of robot-mediated stroke therapy

Robot-mediated therapies offer a new approach to neurorehabilitation. This paper analyses the Fugl-Meyer data from the Gentle/S project and finds that the two intervention phases (sling suspension and robot mediated therapy) have approximately equal value to the further recovery of chronic stroke subjects (on average 27 months post stroke). Both sling suspension and robot mediated interventions show a recovery over baseline and further work is needed to establish the common factors in treatment, and to establish intervention protocols for each that will give individual subjects a maximum level of recovery.

Multivariate analysis of the Fugl-Meyer outcome measures assessing the effectiveness of GENTLE/S robot-mediated stroke therapy

Background: Robot-mediated therapies offer entirely new approaches to neurorehabilitation. In this paper we present the results obtained from trialling the GENTLE/S neurorehabilitation system assessed using the upper limb section of the Fugl-Meyer ( FM) outcome measure. Methods: We demonstrate the design of our clinical trial and its results analysed using a novel statistical approach based on a multivariate analytical model. This paper provides the rational for using multivariate models in robot-mediated clinical trials and draws conclusions from the clinical data gathered during the GENTLE/S study. Results: The FM outcome measures recorded during the baseline ( 8 sessions), robot-mediated therapy ( 9 sessions) and sling-suspension ( 9 sessions) was analysed using a multiple regression model. The results indicate positive but modest recovery trends favouring both interventions used in GENTLE/S clinical trial. The modest recovery shown occurred at a time late after stroke when changes are not clinically anticipated. Conclusion: This study has applied a new method for analysing clinical data obtained from rehabilitation robotics studies. While the data obtained during the clinical trial is of multivariate nature, having multipoint and progressive nature, the multiple regression model used showed great potential for drawing conclusions from this study. An important conclusion to draw from this paper is that this study has shown that the intervention and control phase both caused changes over a period of 9 sessions in comparison to the baseline. This might indicate that use of new challenging and motivational therapies can influence the outcome of therapies at a point when clinical changes are not expected. Further work is required to investigate the effects arising from early intervention, longer exposure and intensity of the therapies. Finally, more function-oriented robot-mediated therapies or sling-suspension therapies are needed to clarify the effects resulting from each intervention for stroke recovery.

Rejoinder to 'Performance of different synchronisation measures in real data: A case study on electroencephalograhic signals

We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga et al. [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga et al. in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga et al. in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

Comment on "Performance of different synchronization measures in real data: A case study on electroencephalographic signals"

We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

Long chain n-3 PUFA-rich meal reduced postprandial measures of arterial stiffness

Background & aims The consumption of long chain n − 3 polyunsaturated fatty acids (LC n − 3 PUFA) is known to be cardio-protective. Data on the influence of LC n − 3 PUFA on arterial stiffness in the postprandial state is limited. The aim of this study was to investigate the acute effects of a LC n − 3 PUFA-rich meal on measures of arterial stiffness. Methods Twenty-five healthy subjects (12 men, 13 women) received a control and a LC n − 3 PUFA-rich meal on two occasions in a random order. Arterial stiffness was measured at baseline, 30, 60, 90, 120, 180 and 240 min after meal consumption by pulse wave analysis and digital volume pulse to derive an augmentation index and a stiffness index respectively. Blood samples were taken for measurement of lipids, glucose and insulin. Results Consumption of the LC n − 3 PUFA-rich meal had an attenuating effect on augmentation index (P = 0.02) and stiffness index (P = 0.03) compared with the control meal. A significant treatment effect (P = 0.036) was seen for plasma non-esterified fatty acids concentrations. Conclusions These data indicate that acute LC n − 3 PUFA-rich meal consumption can improve postprandial arterial stiffness. This has important implications for the beneficial properties of LC n − 3 PUFA and cardiovascular risk reduction.

Spectrally-invariant behavior of zenith radiance around cloud edges simulated by radiative transfer

In a previous paper, we discovered a surprising spectrally-invariant relationship in shortwave spectrometer observations taken by the Atmospheric Radiation Measurement (ARM) program. The relationship suggests that the shortwave spectrum near cloud edges can be determined by a linear combination of zenith radiance spectra of the cloudy and clear regions. Here, using radiative transfer simulations, we study the sensitivity of this relationship to the properties of aerosols and clouds, to the underlying surface type, and to the finite field-of-view (FOV) of the spectrometer. Overall, the relationship is mostly sensitive to cloud properties and has little sensitivity to other factors. At visible wavelengths, the relationship primarily depends on cloud optical depth regardless of cloud phase function, thermodynamic phase and drop size. At water-absorbing wavelengths, the slope of the relationship depends primarily on cloud optical depth; the intercept, by contrast, depends primarily on cloud absorbing and scattering properties, suggesting a new retrieval method for cloud drop effective radius. These results suggest that the spectrally-invariant relationship can be used to infer cloud properties near cloud edges even with insufficient or no knowledge about spectral surface albedo and aerosol properties.

Physical interpretation of the correlation between multi-angle spectral data and canopy height

Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally.