Calculations of the thermodynamic and kinetic properties of LiV3O8

The phase behavior and kinetic pathways of Li1+xV3O8 are investigated by means of density functional theory (DFT) and a cluster expansion (CE) methodology that approximates the system Hamiltonian in order to identify the lowest energy configurations. Although DFT calculations predict the correct ground state for a given composition, both GGA and LDA fail to obtain phase stability consistent with experiment due to strongly localized vanadium 3d electrons. A DFT+U methodology recovers the correct phase stability for an optimized U value of 3.0eV. GGA+U calculations with this value of U predict electronic structures that qualitatively agree with experiment. The resulting calculations indicate solid solution behavior from LiV3O8 to Li2.5V3O8 and two-phase coexistence between Li2.5V3O8 and Li4V3O8. Analysis of the lithiation sequence from LiV3O8 to Li2.5V3O8 reveals the mechanism by which lithium intercalation proceeds in this material. Calculations of lithium migration energies for different lithium concentrations and configurations provides insight into the relevant diffusion pathways and their relationship to structural properties

High-Frame-Rate Power Doppler Ultrasound Is More Sensitive than Conventional Power Doppler in Detecting Rheumatic Vascularisation

Early recognition of joint inflammation will increase treatment efficacy in rheumatoid arthritis (RA). Yet, conventional power Doppler (PD) ultrasound might not be sufficiently sensitive to detect minor inflammation. We investigated the sensitivity of high-frame rate Doppler, combined with singular value decomposition technique, to suppress tissue signals, for microvascular flow in a flow phantom setup and in a proof-of-principle study in healthy controls and in RA patients with different disease activities. In the flow phantom, minimal detectable flow velocity was a factor 3 lower with high-frame-rate PD than with conventional PD ultrasound. In the proof-of-principle study we detected a positive PD signal in all volunteers, diseased or healthy, with high-frame-rate PD ultrasound. We saw a gradual increase in PD signal in RA patients depending on disease activity. In conclusion, high-frame rate Doppler is more sensitive in detecting vascularisation than conventional PD ultrasound

Conceptualizing vulnerability for health effects of the covid-19 pandemic and the associated measures in utrecht and zeist:A concept map

The COVID-19 pandemic and the associated measures have impacted the health of many. Not all population groups are equally vulnerable to such health effects, possibly increasing health inequalities. We performed a group concept mapping procedure to define a common, context-specific understanding of what makes people vulnerable to health effects of the pandemic and the measures. We organized a two-step, blended brainstorming session with locally involved community members, using the brainstorm focus prompt ‘What I think makes people vulnerable for the COVID-19 pandemic and the measures is … ’. We asked participants to generate as many statements as possible. Participants then individually structured (sorted and ranked) these statements. The structuring data was analysed using the groupwisdom™ software and then interpreted by the researchers to generate the concept map. Ninety-eight statements were generated by 19 participants. Sixteen participants completed both structuring tasks. The final concept map consisted of 12 clusters of vulnerability factors, indicating a broad conceptualization of vulnerability during the pandemic. It is being used as a basis for future research and local supportive interventions. Concept mapping is an effective method to arrive at a vulnerability assessment in a community in a short time and, moreover, a method that promotes community engagement

Temporal changes in mindfulness skills and positive and negative affect and their Interrelationships during mindfulness based cognitive therapy for cancer patients

Objectives:  While efficacy research on mindfulness-based interventions in cancer patients is available, research on possible mechanisms of change is lacking. The current study investigated general and week-to-week changes and interrelations in mindfulness and positive and negative affect in Mindfulness-Based Cognitive Therapy (MBCT) for cancer patients.  Methods:  In total, 163 cancer patients completed face-to-face or online MBCT. Mindfulness and positive and negative affect were measured weekly during the intervention. Autoregressive latent trajectory models were used to evaluate general and week-to-week effects.  Results:  Overall, mindfulness and positive affect increased, and negative affect decreased during MBCT. Higher general levels of mindfulness were associated with higher general levels of positive affect. Regarding week-to-week effects, positive affect in weeks 3, 7, and 8 predicted an increase in mindfulness in the following week. Various general relations were observed between mindfulness and negative affect, showing that higher mindfulness was related to less negative affect. To the contrary, week-to-week effects showed higher mindfulness consistently predicted increased negative affect in the subsequent week.  Conclusions:  In cancer patients, mindfulness appeared to be more robustly related to negative than to positive affect. Furthermore, mindfulness in one week was related to an increase of negative affect in the following week, possibly due to turning towards previously suppressed negative emotions. However, when focusing on the whole course from start to end, the increase of mindfulness was related to a decrease of negative affect, possibly due to acceptance of and exposure to negative emotions. Our findings reveal the complexity of mechanisms of MBCT and illustrate the necessity of sophisticated models with longitudinal measurements to truly elucidate these mechanisms.  Trial Registration: Clinical Trials.gov: NCT02138513

The effect of unresolved binaries on globular cluster proper-motion dispersion profiles

High-precision kinematic studies of globular clusters require an accurate knowledge of all possible sources of contamination. Amongst other sources, binary stars can introduce systematic biases in the kinematics. Using a set of Monte Carlo cluster simulations with different concentrations and binary fractions, we investigate the effect of unresolved binaries on proper-motion dispersion profiles, treating the simulations like HST propermotion samples. Since globular clusters evolve towards a state of partial energy equipartition, more massive stars lose energy and decrease their velocity dispersion. As a consequence, on average, binaries have a lower velocity dispersion, since they are more massive kinematic tracers. We show that, in the case of clusters with high binary fraction (initial binary fraction of 50%) and high concentration (i.e., closer to energy equipartition), unresolved binaries introduce a color-dependent bias in the velocity dispersion of main-sequence stars of the order of 0.1-0.3 km s^-1 (corresponding to 1 − 6% of the velocity dispersion), with the reddest stars having a lower velocity dispersion, due to the higher fraction of contaminating binaries. This bias depends on the ability to distinguish binaries from single stars, on the details of the color-magnitude diagram and the photometric errors. We apply our analysis to the HSTPROMO data set of NGC 7078 (M15) and show that no effect ascribable to binaries is observed, consistent with the low binary fraction of the cluster. Our work indicates that binaries do not significantly bias proper-motion velocity-dispersion profiles, but should be taken into account in the error budget of kinematic analyses

Raman Spectroscopy Study of alpha-, beta-, gamma-NaxCoO2 and gamma-(Ca,Sr)xCoO2

Raman spectroscopy measurements have been performed on alpha-, beta-, gamma-NaxCoO2 phases differing in their stacking of CoO6 octahedra along the c-axis direction. The results demonstrate that, in general, there are five active phonons for gamma-Na0.75CoO2, two Raman active phonons for alpha-NaCoO2, and four Raman active phonons for beta-NaCoO2. We have also performed Raman scattering measurements on several gamma-(Ca,Sr)xCoO2 (0.15 <= x <= 0.35) samples which show well-defined intercalated Ca/Sr-ordering. The experimental data show that the intercalated cation ordering could result in visible alterations on Raman spectral structures. The observations of the spectral changes along with the variation of the CoO6 stacking, as well as the intercalated Sr/Ca ordering suggest that the interlayer interaction plays an important role for understanding the lattice dynamics in this layered system.Comment: 23 pages, 5 figures, Physical Review B, in pres

Path finding on a spherical self-organizing map using distance transformations

Spatialization methods create visualizations that allow users to analyze high-dimensional data in an intuitive manner and facilitates the extraction of meaningful information. Just as geographic maps are simpli ed representations of geographic spaces, these visualizations are esssentially maps of abstract data spaces that are created through dimensionality reduction. While we are familiar with geographic maps for path planning/ nding applications, research into using maps of high-dimensional spaces for such purposes has been largely ignored. However, literature has shown that it is possible to use these maps to track temporal and state changes within a high-dimensional space. A popular dimensionality reduction method that produces a mapping for these purposes is the Self-Organizing Map. By using its topology preserving capabilities with a colour-based visualization method known as the U-Matrix, state transitions can be visualized as trajectories on the resulting mapping. Through these trajectories, one can gather information on the transition path between two points in the original high-dimensional state space. This raises the interesting question of whether or not the Self-Organizing Map can be used to discover the transition path between two points in an n-dimensional space. In this thesis, we use a spherically structured Self-Organizing Map called the Geodesic Self-Organizing Map for dimensionality reduction and the creation of a topological mapping that approximates the n-dimensional space. We rst present an intuitive method for a user to navigate the surface of the Geodesic SOM. A new application of the distance transformation algorithm is then proposed to compute the path between two points on the surface of the SOM, which corresponds to two points in the data space. Discussions will then follow on how this application could be improved using some form of surface shape analysis. The new approach presented in this thesis would then be evaluated by analyzing the results of using the Geodesic SOM for manifold embedding and by carrying out data analyses using carbon dioxide emissions data