Effective LAI and CHP of a single tree from small-footprint full-waveform LiDAR

This letter has tested the canopy height profile (CHP) methodology as a way of effective leaf area index (LAIe) and vertical vegetation profile retrieval at a single-tree level. Waveform and discrete airborne LiDAR data from six swaths, as well as from the combined data of six swaths, were used to extract the LAIe of a single live Callitris glaucophylla tree. LAIe was extracted from raw waveform as an intermediate step in the CHP methodology, with two different vegetation-ground reflectance ratios. Discrete point LAIe estimates were derived from the gap probability using the following: 1) single ground returns and 2) all ground returns. LiDAR LAIe retrievals were subsequently compared to hemispherical photography estimates, yielding mean values within ±7% of the latter, depending on the method used. The CHP of a single dead Callitris glaucophylla tree, representing the distribution of vegetation material, was verified with a field profile manually reconstructed from convergent photographs taken with a fixed-focal-length camera. A binwise comparison of the two profiles showed very high correlation between the data reaching R2 of 0.86 for the CHP from combined swaths. Using a study-area-adjusted reflectance ratio improved the correlation between the profiles, but only marginally in comparison to using an arbitrary ratio of 0.5 for the laser wavelength of 1550 nm.

A single-column model ensemble approach applied to the TWP-ICE experiment

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

Flexible selection of a single treatment incorporating short-term endpoint information in a phase II/III clinical trial

Seamless phase II/III clinical trials in which an experimental treatment is selected at an interim analysis have been the focus of much recent research interest. Many of the methods proposed are based on the group sequential approach. This paper considers designs of this type in which the treatment selection can be based on short-term endpoint information for more patients than have primary endpoint data available. We show that in such a case, the familywise type I error rate may be inflated if previously proposed group sequential methods are used and the treatment selection rule is not specified in advance. A method is proposed to avoid this inflation by considering the treatment selection that maximises the conditional error given the data available at the interim analysis. A simulation study is reported that illustrates the type I error rate inflation and compares the power of the new approach with two other methods: a combination testing approach and a group sequential method that does not use the short-term endpoint data, both of which also strongly control the type I error rate. The new method is also illustrated through application to a study in Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

EMD performance comparison: single vs double floating points

Empirical mode decomposition (EMD) is a data-driven method used to decompose data into oscillatory components. This paper examines to what extent the defined algorithm for EMD might be susceptible to data format. Two key issues with EMD are its stability and computational speed. This paper shows that for a given signal there is no significant difference between results obtained with single (binary32) and double (binary64) floating points precision. This implies that there is no benefit in increasing floating point precision when performing EMD on devices optimised for single floating point format, such as graphical processing units (GPUs).

Acute benefits of the microbial-derived isoflavone metabolite equol on arterial stiffness in men prospectively recruited according to equol producer phenotype: a double-blind randomized controlled trial

There is much speculation with regard to the potential cardioprotective benefits of equol, a microbial-derived metabolite of the isoflavone daidzein, which is produced in the large intestine after soy intake in 30% of Western populations. Although cross-sectional and retrospective data support favorable associations between the equol producer (EP) phenotype and cardiometabolic health, few studies have prospectively recruited EPs to confirm this association. The aim was to determine whether the acute vascular benefits of isoflavones differ according to EP phenotype and subsequently investigate the effect of providing commercially produced S-(–)equol to non-EPs. We prospectively recruited male EPs and non-EPs (n = 14/ group) at moderate cardiovascular risk into a double-blind, placebocontrolled crossover study to examine the acute effects of soy isoflavones (80-mg aglycone equivalents) on arterial stiffness [carotid-femoral pulse-wave velocity (cfPWV)], blood pressure, endothelial function (measured by using the EndoPAT 2000; Itamar Medical), and nitric oxide at baseline (0 h) and 6 and 24 h after intake. In a separate assessment, non-EPs consumed 40 mg S-(–)equol with identical vascular measurements performed 2 h after intake. After soy intake, cfPWV significantly improved in EPs at 24 h (cfPWV change from 0 h: isoflavone, 20.2 6 0.2 m/s; placebo, 0.6 6 0.2 m/s; P , 0.01), which was significantly associated with plasma equol concentrations (R = 20.36, P = 0.01). No vascular effects were observed in EPs at 6 h or in non-EPs at any time point. Similarly, no benefit of commercially produced S-(–)equol was observed in non-EPs despite mean plasma equol concentrations reaching 3.2 mmol/L. Acute soy intake improved cfPWV in EPs, equating to an 11–12% reduced risk of cardiovascular disease if sustained. However, a single dose of commercially produced equol had no cardiovascular benefits in non-EPs. These data suggest that the EP phenotype is critical in unlocking the vascular benefits of equol in men, and long-term trials should focus on confirming the implications of EP phenotype on cardiovascular health. This trial was registered at clinicaltrials.gov as NCT01530893. Am J Clin Nutr doi: 10.3945/ajcn.115.125690.

Secoiridoids delivered as olive leaf extract induce acute improvements in human vascular function and reduction of an inflammatory cytokine: a randomised, double-blind, placebo-controlled, cross-over trial

The leaves of the olive plant (Olea europaea) are rich in polyphenols, of which oleuropein and hydroxytyrosol (HT) are most characteristic. Such polyphenols have been demonstrated to favourably modify a variety of cardiovascular risk factors. The aim of the present intervention was to investigate the influence of olive leaf extract (OLE) on vascular function and inflammation in a postprandial setting and to link physiological outcomes with absorbed phenolics. A randomised, double-blind, placebo-controlled, cross-over, acute intervention trial was conducted with eighteen healthy volunteers (nine male, nine female), who consumed either OLE (51 mg oleuropein; 10mg HT), or a matched control (separated by a 4-week wash out) on a single occasion. Vascular function was measured by digital volume pulse (DVP), while blood collected at baseline, 1, 3 and 6 h was cultured for 24 h in the presence of lipopolysaccharide in order to investigate effects on cytokine production. Urine was analysed for phenolic metabolites by HPLC. DVP-stiffness index and ex vivo IL-8 production were significantly reduced (P < 0.05) after consumption of OLE compared to the control. These effects were accompanied by the excretion of several phenolic metabolites, namely HT and oleuropein derivatives, which peaked in urine after 8-24 h. The present study provides the first evidence that OLE positively modulates vascular function and IL-8 production in vivo, adding to growing evidence that olive phenolics could be beneficial for health.