Isophote curves on timelike surfaces in Minkowski 3-space

Isophote comprises a locus of the surface points whose normal vectors make a constant angle with a fixed vector. In this paper, isophote curves are studied on timelike surfaces in Minkowski 3-space E31. The axises of spacelike and timelike isophote curves are found via their Darboux frames. Subsequently, the relationship between isophotes and slant helices is shown on timelike surfaces.Comment: 11 pages. arXiv admin note: text overlap with arXiv:1203.438

Direct Measurement of the Fermi Energy in Graphene Using a Double Layer Structure

We describe a technique which allows a direct measurement of the relative Fermi energy in an electron system using a double layer structure, where graphene is one of the two layers. We illustrate this method by probing the Fermi energy as a function of density in a graphene monolayer, at zero and in high magnetic fields. This technique allows us to determine the Fermi velocity, Landau level spacing, and Landau level broadening in graphene. We find that the N=0 Landau level broadening is larger by comparison to the broadening of upper and lower Landau levels.Comment: 5 pages, 4 figure

Assessing Implementation of Maternal and Perinatal Death Surveillance and Response in Rwanda

Contains fulltext : 221427.pdf (publisher's version ) (Open Access

Maternal and Perinatal Outcomes among Maternity Waiting Home Users and Non-Users in Rural Rwanda

Most maternal and perinatal deaths could be prevented through timely access to skilled birth attendants. Women should access appropriate obstetric care during pregnancy, labor, and puerperium. Maternity waiting homes (MWHs) permit access to emergency obstetric care when labor starts. This study compared maternal and perinatal outcomes among MWH users and non-users through a retrospective cohort study. Data were collected through obstetric chart reviews and analyzed using STATA version 15. Of the 8144 deliveries reported between 2015 and 2019, 1305 women had high-risk pregnancies and were included in the study. MWH users had more spontaneous vaginal deliveries compared to non-users (38.6% versus 16.8%) and less cesarean sections (57.7% versus 76.7%). Maternal morbidities such as postpartum hemorrhage occurred less frequently among users than non-users (2.13% versus 5.64%). Four women died among non-users while there was no death among users. Non-users had more stillbirths than users (7.68% versus 0.91%). The MWH may have contributed to the observed differences in outcomes. However, many women with high risk pregnancies did not use the MWH, indicating a probable gap in awareness, usefulness, or their inability to stay due to other responsibilities at home. Use of MWHs at scale could improve maternal and perinatal outcomes in Rwanda

Holmium Nanoparticles: Preparation and In Vitro Characterization of a New Device for Radioablation of Solid Malignancies

# The Author(s) 2010. This article is published with open access at Springerlink.com Purpose The present study introduces the preparation and in vitro characterization of a nanoparticle device comprising holmium acetylacetonate for radioablation of unresectable solid malignancies. Methods HoAcAc nanoparticles were prepared by dissolving holmium acetylacetonate in chloroform, followed by emulsification in an aqueous solution of a surfactant and evaporation of W. Bult: R. Varkevisser: P. R. Luijten: A. D. van het Schip

The influence of driver’s mood on car following and glance behaviour: Using cognitive load as an intervention

Driving safety relies on a driver’s ability to maintain their attentional focus and that mood is one of the factors which influences this ability. This driving simulator study used mind wandering theory to understand the changes in car following behaviour and driver glance patterns when affected by neutral, happy, sad and angry moods during car following. Two types of cognitive load were used to investigate ways of disengaging drivers from the mind wandering state. The moods were induced via music and mental imagery and assessed via self-reports and physiological measures. The results show that mood valence and arousal have different effects on driving safety, with negative moods resulting in the most dangerous driving, regardless of arousal. The cognitive load, in some cases, disengaged drivers from mood-related mind wandering. However, more detailed research is needed to understand the amount of load necessary for this disengagement in different moods. The importance of using driving-related measures together with glance patterns in mood research was highlighted to overcome ambiguities resulting from conclusions based on single measurements

Defect model for the mixed mobile ion effect

This paper presents a new defect model for the mixed mobile ion effect. The essential physical concept involved is that simultaneous migration of two unlike mobile ions in mixed ionic glass is accompanied by expansion or contraction of the guest-occupied sites with distortion of surrounding glass matrix; in many cases, an intensity of the local stresses in glass matrix surrounding ionic sites occupied by foreign ions is much greater than, or at least comparable to the glass network binding energy. Hence, when the stress exceeds the breaking threshold, relaxation occurs almost immediately via the rupture of the bonds in the nearest glass matrix with generation of pairs of intrinsic structural defects. The specificity of the mechanism of defect generation leads to the clustering of negatively charged defects, so that rearranged sites act as high energy anion traps in glass matrix. This results in the immobilization of almost all minority mobile species and part of majority mobile species, so mixed mobile ion glass behaves as single mobile ion glass of much lower concentration of charge carriers. Generation of defects leads also to the depolymerization of glass network, which in turn results in the reduction of the glass viscosity and Tg as well as in the compaction of glass structure (thermometer effect). The magnitude of the mixed mobile ion effect is defined by the size mismatch of unlike mobile ions, their total and relative concentrations, the binding energy of the glass-forming network, and temperature. Although the proposed model is based upon the exploration of alkali silicate glass-forming system, the approach developed here can be easily adopted to other mixed ionic systems such as crystalline and even liquid ionic conductors.Comment: 33 pages, 2 figure

On the Extraction and Analysis of Graphs From Resting-State fMRI to Support a Correct and Robust Diagnostic Tool for Alzheimer's Disease

The diagnosis of Alzheimer's disease (AD), especially in the early stage, is still not very reliable and the development of new diagnosis tools is desirable. A diagnosis based on functional magnetic resonance imaging (fMRI) is a suitable candidate, since fMRI is non-invasive, readily available, and indirectly measures synaptic dysfunction, which can be observed even at the earliest stages of AD. However, the results of previous attempts to analyze graph properties of resting state fMRI data are contradictory, presumably caused by methodological differences in graph construction. This comprises two steps: clustering the voxels of the functional image to define the nodes of the graph, and calculating the graph's edge weights based on a functional connectivity measure of the average cluster activities. A variety of methods are available for each step, but the robustness of results to method choice, and the suitability of the methods to support a diagnostic tool, are largely unknown. To address this issue, we employ a range of commonly and rarely used clustering and edge definition methods and analyze their graph theoretic measures (graph weight, shortest path length, clustering coefficient, and weighted degree distribution and modularity) on a small data set of 26 healthy controls, 16 subjects with mild cognitive impairment (MCI) and 14 with Alzheimer's disease. We examine the results with respect to statistical significance of the mean difference in graph properties, the sensitivity of the results to model and parameter choices, and relative diagnostic power based on both a statistical model and support vector machines. We find that different combinations of graph construction techniques yield contradicting, but statistically significant, relations of graph properties between health conditions, explaining the discrepancy across previous studies, but casting doubt on such analyses as a method to gain insight into disease effects. The production of significant differences in mean graph properties turns out not to be a good predictor of future diagnostic capacity. Highest predictive power, expressed by largest negative surprise values, are achieved for both atlas-driven and data-driven clustering (Ward clustering), as long as graphs are small and clusters large, in combination with edge definitions based on correlations and mutual information transfer