Second opinion NuStar terminal expansion

In this report a second opinion is developed for the Environmental Impact Assessment NuStar terminal expansion (at St. Eustatius). Only the marine ecology part of the EIA report is evaluated focusing on the impacts reported for marine reserves, reef- and sea-grass habitat, conchs, turtles, marine mammal and fish. The criteria used are: completeness, consistence, transparency, ecological soundness, and relevance of the foreseen impacts resulting from the terminal expansion. When applying these criteria we have found that most of the impact assessments were incomplete (missing information and data, missing expected impacts). Reference base line data has been incompletely collected. Furthermore, many of the assessments were not transparent (based on the information given in the EIA we could not come to the same conclusion). Also we found that the reasoning to come to a conclusion in the EIA was not ecologically sound in many cases (e.g. mobile species are not affected by habitat loss because they can move out the area instead of describing an effect on the distribution area and thus on the abundance or density of the species). In a few cases assessments scored not relevant or were not assessed in a consistent way. Furthermore, we found that not all expected (potential) impacts were assessed and that those assessed were mainly qualitatively assessed only. Data on pressures was incomplete as was data on ecological receptors, and some publically available data was not used. At the end of this report we list these data needs and missing impact assessments

Seasonal patterns in mindfulness in people with seasonal affective disorder (SAD)

Background: Mindfulness-based cognitive therapy (MBCT) is a well-known, effective treatment in the prevention of relapse in Major Depression Disorder (MDD). However, a recent study in people with Seasonal Affective Disorder (SAD) showed that MBCT given in spring was ineffective in preventing a next depressive episode. To test the hypothesis that people with SAD may experience sufficient levels of mindfulness in spring and therefore less benefit from MBCT, this study examines variations in levels of mindfulness over seasons. Methods: This longitudinal prospective study followed 77 people with SAD over a two-year period. Participants filled out a self-report questionnaire, Five Facet Mindfulness Questionnaire (FFMQ) on a quarterly basis. Results: Levels of mindfulness differed throughout the seasons, with overall results suggesting lower levels of mindfulness in winter. Limitations: The results are limited by the small sample size and varying levels of mindfulness over the two years of the study period. Conclusion: Findings suggest a seasonal component in levels of mindfulness exists, implying that people with SAD are less mindful during the winter compared to other seasons. Future research is needed to examine to what extent the motivation of people with SAD to participate in MBCT and benefit from it is higher in the winter

Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution

We propose two strategies to improve the quality of tractography results computed from diffusion weighted magnetic resonance imaging (DW-MRI) data. Both methods are based on the same PDE framework, defined in the coupled space of positions and orientations, associated with a stochastic process describing the enhancement of elongated structures while preserving crossing structures. In the first method we use the enhancement PDE for contextual regularization of a fiber orientation distribution (FOD) that is obtained on individual voxels from high angular resolution diffusion imaging (HARDI) data via constrained spherical deconvolution (CSD). Thereby we improve the FOD as input for subsequent tractography. Secondly, we introduce the fiber to bundle coherence (FBC), a measure for quantification of fiber alignment. The FBC is computed from a tractography result using the same PDE framework and provides a criterion for removing the spurious fibers. We validate the proposed combination of CSD and enhancement on phantom data and on human data, acquired with different scanning protocols. On the phantom data we find that PDE enhancements improve both local metrics and global metrics of tractography results, compared to CSD without enhancements. On the human data we show that the enhancements allow for a better reconstruction of crossing fiber bundles and they reduce the variability of the tractography output with respect to the acquisition parameters. Finally, we show that both the enhancement of the FODs and the use of the FBC measure on the tractography improve the stability with respect to different stochastic realizations of probabilistic tractography. This is shown in a clinical application: the reconstruction of the optic radiation for epilepsy surgery planning

Sensitivity to change of the Beck Depression Inventory versus the Inventory of Depressive Symptoms

Background: In a previous study which made a comparison between disorder-specific and generic instruments to assess outcome of treatments for depression, the Beck Depression Inventory, Second Edition (BDI-II) seemed to be more sensitive to change than the Inventory of Depressive Symptoms- Self Rating (IDS-SR). Methods: A set with longitudinal data from Routine Outcome Monitoring (n=144) were analyzed with multilevel models with random intercepts. The sensitivity to change of two disorder-specific instruments, the BDI-II and the IDS-SR, were compared head to head. Results: The BDI-II was more sensitive to change when measuring treatment outcome compared to the IDS-SR. The BDI-II decreases significantly more over time than the IDS-SR: the average decrease per week for the IDS-SR is -.012 (95%CI -0.015, -0.009) and for the BDI-II it is -.017 (95%CI -0.021, -0.014). Limitations: Conclusions can only be preliminary due to a small sample size. Conclusions: Treatment outcomes measured with questionnaires may differ depending on the degree of sensitivity to change of the instruments

EDAQ : DLV. Vragenlijst Evaluatie Dagelijkse Activiteit (Dutch language version of the Evaluation of Daily Activity Questionnaire)

The Dutch language version of the Evaluation of Daily Activity Questionnaire (EDAQ) is a self-report outcome measure, which people complete at home in their own time and then return to the clinician/ researcher. It has been validated for use with people with arthritis and musculoskeletal conditions in the UK, and with people with rheumatoid arthritis in the Netherlands. It can be used for clinical, audit and research purposes. It includes three parts. Part 1 consists of 10 numeric rating scales evaluating aspects of body functions (e.g. pain, fatigue, movement limitations). Part 2 consists of 14 domains assessing activity and participation abilities/ restrictions with and without the use of ergonomic approaches. Part 3 (optional) is about assistive device use. It is available in two forms: parts 1 to 3 and parts 1 and 2 only. Usually, the EDAQ parts 1 and 2 is used for most clinical and research purposes. The updated EDAQ Manual v3 (2018) explains how to use and score the EDAQ, with scoring examples (http://usir.salford.ac.uk/30752/). Rasch Transformation Tables are available in the EDAQ Manual v2 Supplement 1 and Supplement 2. An explanatory leaflet for clients is also available in USIR here under Monographs

Modelling representation errors of atmospheric CO2 mixing ratios at a regional scale

Inverse modelling of carbon sources and sinks requires an accurate quality estimate of the modelling framework to obtain a realistic estimate of the inferred fluxes and their uncertainties. So-called "representation errors" result from our inability to correctly represent point observations with simulated average values of model grid cells. They may add substantial uncertainty to the interpretation of atmospheric CO2 mixing ratio data. We simulated detailed variations in the CO2 mixing ratios with a high resolution (2 km) mesoscale model (RAMS) to estimate the representation errors introduced at larger model grid sizes of 10 100 km. We found that meteorology is the main driver of representation errors in our study causing spatial and temporal variations in the error estimate. Within the nocturnal boundary layer, the representation errors are relatively large and mainly caused by unresolved topography at lower model resolutions. During the day, convective structures, mesoscale circulations, and surface CO2 flux variability were found to be the main sources of representation errors. Interpreting observations near a mesoscale circulation as representative for air with the correct footprint relative to the front can reduce the representation error substantially. The remaining representation error is 0.5 1.5 ppm at 20 100 km resolution