Targeting hyperarousal: Mantram Repetition Program for PTSD in US veterans.

Background: Hyperarousal appears to play an important role in the development and maintenance of posttraumatic stress disorder (PTSD) symptoms, but current evidence-based treatments appear to address this symptom type less effectively than the other symptom clusters. The Mantram Repetition Program (MRP) is a meditation-based intervention that has previously been shown to improve symptoms of posttraumatic stress disorder (PTSD) and may be especially helpful for hyperarousal. If MRP is an effective tool for decreasing this often treatment-resistant symptom cluster, it may become an important clinical tool. Objective: The goal of this secondary analysis was to examine the effect of the MRP on hyperarousal and other PTSD symptom clusters and to examine hyperarousal as a mediator of treatment response. Method: Secondary analyses were conducted on data from a randomized controlled trial in which Veterans with PTSD (n = 173) were assigned to the MRP or a non-specific psychotherapy control and assessed pre-treatment, post-treatment and 8 weeks after treatment completion. The impact of the interventions on PTSD symptom clusters was examined, and time-lagged hierarchical linear modelling was applied to examine alternative mediation models. Results: All PTSD symptom clusters improved in both treatments. MRP led to greater reductions in hyperarousal at post-treatment (Hedge's g = 0.57) and follow-up (Hedge's g = 0.52), and in numbing at post-treatment (Hedge's g = 0.47). Hyperarousal mediated reductions in the composite of the other PTSD symptom clusters. Although the reverse model was significant as well, the effect was weaker in this direction. Conclusion: Interventions focused on the management of hyperarousal may play an important role in recovery from PTSD. The MRP appears efficacious in reducing hyperarousal, and thereby impacting other PTSD symptom clusters, as one pathway to facilitating recovery

Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling

Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future

Triangulating Horizontal Inequality: Towards Improved Conflict Analysis.

Does economic inequality cause civil war? Deviating from individualist measures of inequality such as the Gini coefficient, recent studies have found a statistical link between group-level inequalities and conflict onset. Yet, this connection remains controversial, not least because of the difficulties associated with conceptualizing and measuring group-level differences in development. In an effort to overcome weaknesses afflicting specific methods of measurement, we introduce a new composite indicator that exploits the strengths of three sources of data. The first step of our method combines geocoded data from the G-Econ project with night lights emissions data from satellites. In a second step, we bring together the combined spatial values with survey estimates in order to arrive at an improved measure of group-level inequality that is both more accurate and robust than any one of the component measures. We evaluate the effect of the combined indicator and its components on the onset of civil violence. As expected, the combined index yields stronger results as more information becomes available, thus confirming the initial hypothesis that horizontal economic inequality does drive conflict in the case of groups that are relatively poorer compared to the country average. Furthermore, these findings appear to be considerably more robust than those relying on a single data source.Swiss National Science FoundationAlexander von Humboldt Foundatio

Simulation of underground gravity gradients from stochastic seismic fields

We present results obtained from a finite-element simulation of seismic displacement fields and of gravity gradients generated by those fields. The displacement field is constructed by a plane wave model with a 3D isotropic stochastic field and a 2D fundamental Rayleigh field. The plane wave model provides an accurate representation of stationary fields from distant sources. Underground gravity gradients are calculated as acceleration of a free test mass inside a cavity. The results are discussed in the context of gravity-gradient noise subtraction in third generation gravitational-wave detectors. Error analysis with respect to the density of the simulated grid leads to a derivation of an improved seismometer placement inside a 3D array which would be used in practice to monitor the seismic field.Comment: 24 pages, 12 figure

The influence of DACCIWA radiosonde data on the quality of ECMWF analyses and forecasts over southern West Africa

During the DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa) field campaign ∼900 radiosondes were launched from 12 stations in southern West Africa from 15 June to 31 July 2016. Subsequently, data-denial experiments were conducted using the Integrated Forecasting System of the European Centre for Medium-range Weather Forecasts (ECMWF) to assess the radiosondes\u27 impact on the quality of analyses and forecasts. As observational reference, satellite-based estimates of rainfall and outgoing long-wave radiation (OLR) as well as the radiosonde measurements themselves are used. With regard to the analyses, the additional observations show positive impacts onwinds throughout the troposphere and lower stratosphere, while large lower-tropospheric cold and dry biases are hardly reduced. Nonetheless, downstream, that is farther inland from the radiosonde stations,we find a significant increase (decrease) in low-level night-time temperatures (monsoon winds) when incorporating the DACCIWA observations, suggesting a possible linkage via weaker cold air advection fromthe Gulf of Guinea. The associated lower relative humidity leads to reduced cloud cover in the DACCIWA analysis. Closer to the coast and over Benin and Togo, DACCIWA observations increase low-level specific humidity and precipitable water, possibly due to changes in advection and vertical mixing. During daytime, differences between the two analyses are generally smaller at low levels. With regard to the forecasts, the impact of the additional observations is lost after a day or less. Moderate improvements occur in low-level wind and temperature but also in rainfall over the downstream Sahel, while impacts on OLR are ambiguous. The changes in precipitation appear to also affect high-level cloud cover and the tropical easterly jet. The overall rather small observation impact suggests that model and data assimilation deficits are the main limiting factors for better forecasts inWest Africa. The new observations and physical understanding from DACCIWA can hopefully contribute to reducing these issues

Continuous data assimilation for global numerical weather prediction

A new configuration of the European Centre for Medium-Range Weather Forecasts (ECMWF) incremental 4D-Var data assimilation (DA) system is introduced which builds upon the quasi-continuous DA concept proposed in the mid-1990s. Rather than working with a fixed set of observations, the new 4D-Var configuration exploits the near-continuous stream of incoming observations by introducing recently arrived observations at each outer loop iteration of the assimilation. This allows the analysis to benefit from more recent observations. Additionally, by decoupling the start time of the DA calculations from the observational data cut-off time, real-time forecasting applications can benefit from more expensive analysis configurations that previously could not have been considered. In this work we present results of a systematic comparison of the performance of a Continuous DA system against that of two more traditional baseline 4D-Var configurations. We show that the quality of the analysis produced by the new, more continuous configuration is comparable to that of a conventional baseline that has access to all of the observations in each of the outer loops, which is a configuration not feasible in real-time operational numerical weather prediction. For real-time forecasting applications, the Continuous DA framework allows configurations which clearly outperform the best available affordable non-continuous configuration. Continuous DA became operational at ECMWF in June 2019 and led to significant 2 to 3% reductions in medium-range forecast root mean square errors, which is roughly equivalent to 2-3 hr of additional predictive skill.Peer reviewe

A short artificial antimicrobial peptide shows potential to prevent or treat bone infections.

Infection of bone is a severe complication due to the variety of bacteria causing it, their resistance against classical antibiotics, the formation of a biofilm and the difficulty to eradicate it. Antimicrobial peptides (AMPs) are naturally occurring peptides and promising candidates for treatment of joint infections. This study aimed to analyze the effect of short artificial peptides derived from an optimized library regarding (1) antimicrobial effect on different bacterial species, (2) efficacy on biofilms, and (3) effect on osteoblast‑like cells. Culturing the AMP-modifications with Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa, Staphylococcus aureus (including clinical isolates of MRSA and MSSA) and Staphylococcus epidermidis identified one candidate that was most effective against all bacteria. This AMP was also able to reduce biofilm as demonstrated by FISH and microcalorimetry. Osteoblast viability and differentiation were not negatively affected by the AMP. A cation concentration comparable to that physiologically occurring in blood had almost no negative effect on AMP activity and even with 10% serum bacterial growth was inhibited. Bacteria internalized into osteoblasts were reduced by the AMP. Taken together the results demonstrate a high antimicrobial activity of the AMP even against bacteria incorporated in a biofilm or internalized into cells without harming human osteoblasts