Ring-current maps for benzenoids : comparisons, contradictions, and a versatile combinatorial model

As a key diagnostic property of benzenoids and other polycyclic hydrocarbons, induced ring current has inspired diverse approaches for calculation, modeling, and interpretation. Grid-based methods include the ipsocentric ab initio calculation of current maps, and its surrogate, the pseudo-π model. Graph-based models include a family of conjugated-circuit (CC) models and the molecular-orbital Hückel-London (HL) model. To assess competing claims for physical relevance of derived current maps for benzenoids, a protocol for graph-reduction and comparison was devised. Graph reduction of pseudo-π grid maps highlights their overall similarity to HL maps, but also reveals systematic differences. These are ascribed to unavoidable pseudo-π proximity limitations for benzenoids with short nonbonded distances, and to poor continuity of pseudo-π current for classes of benzenoids with fixed bonds, where single-reference methods can be unreliable. Comparison between graph-based approaches shows that the published CC models all shadow HL maps reasonably well for most benzenoids (as judged by L1-, L2-, and L∞-error norms on scaled bond currents), though all exhibit physically implausible currents for systems with fixed bonds. These comparisons inspire a new combinatorial model (Model W) based on cycle decomposition of current, taking into account the two terms of lowest order that occur in the characteristic polynomial. This improves on all pure-CC models within their range of applicability, giving excellent adherence to HL maps for all Kekulean benzenoids, including those with fixed bonds (halving the rms discrepancy against scaled HL bond currents, from 11% in the best CC model, to 5% for the set of 18 360 Kekulean benzenoids on up to 10 hexagonal rings). Model W also has excellent performance for open-shell systems, where currents cannot be described at all by pure CC models (4% rms discrepancy against scaled HL bond currents for the 20112 non-Kekulean benzenoids on up to 10 hexagonal rings). Consideration of largest and next-to-largest matchings is a useful strategy for modeling and interpretation of currents in Kekulean and non-Kekulean benzenoids (nanographenes)

Loneliness, social relations and health and wellbeing in deprived communities

There is growing policy concern about the extent of loneliness in advanced societies, and its prevalence among various social groups. This study looks at loneliness among people living in deprived communities, where there may be additional barriers to social engagement including low incomes, fear of crime, poor services and transient populations. The aim was to examine the prevalence of loneliness, and also its associations with different types of social contacts and forms of social support, and its links to self-reported health and wellbeing in the population group. The method involved a cross-sectional survey of 4,302 adults across 15 communities, with the data analysed using multinomial logistic regression controlling for sociodemographics, then for all other predictors within each domain of interest. Frequent feelings of loneliness were more common among those who: had contact with family monthly or less; had contact with neighbours weekly or less; rarely talked to people in the neighbourhood; and who had no available sources of practical or emotional support. Feelings of loneliness were most strongly associated with poor mental health, but were also associated with long-term problems of stress, anxiety and depression, and with low mental wellbeing, though to a lesser degree. The findings are consistent with a view that situational loneliness may be the product of residential structures and resources in deprived areas. The findings also show that neighbourly behaviours of different kinds are important for protecting against loneliness in deprived communities. Familiarity within the neighbourhood, as active acquaintance rather than merely recognition, is also important. The findings are indicative of several mechanisms that may link loneliness to health and wellbeing in our study group: loneliness itself as a stressor; lonely people not responding well to the many other stressors in deprived areas; and loneliness as the product of weak social buffering to protect against stressors

Reverse Monte Carlo modeling of amorphous silicon

An implementation of the Reverse Monte Carlo algorithm is presented for the study of amorphous tetrahedral semiconductors. By taking into account a number of constraints that describe the tetrahedral bonding geometry along with the radial distribution function, we construct a model of amorphous silicon using the reverse monte carlo technique. Starting from a completely random configuration, we generate a model of amorphous silicon containing 500 atoms closely reproducing the experimental static structure factor and bond angle distribution and in improved agreement with electronic properties. Comparison is made to existing Reverse Monte Carlo models, and the importance of suitable constraints beside experimental data is stressed.Comment: 6 pages, 4 PostScript figure

Time-Varying Dark Energy Constraints From the Latest SN Ia, BAO and SGL

Based on the latest SNe Ia data provided by Hicken et al. (2009) with using MLCS17 light curve fitter, together with the Baryon Acoustic Oscillation(BAO) and strong gravitational lenses(SGL), we investigate the constraints on the dark energy equation-of-state parameter $w$ in the flat universe, especially for the time-varying case $w(z)=w_0+w_zz/(1+z)$. The constraints from SNe data alone are found to be: (a) $(\Omega_M, w)=(0.358, -1.09)$ as the best-fit results; (b) $(w_0, w_z)=(-0.73^{+0.23}_{-0.97}, 0.84^{+1.66}_{-10.34})$ for the two parameters in the time-varying case after marginalizing the parameter $\Omega_M$; (c) the likelihood of parameter $w_z$ has a high non-Gaussian distribution; (d) an extra restriction on $\Omega_M$ is necessary to improve the constraint of the SNe Ia data on the parameters ($w_0$, $w_z$). A joint analysis of SNe Ia data and BAO is made to break the degeneracy between $w$ and $\Omega_M$, and leads to the interesting maximum likelihoods $w_0 = -0.94$ and $w_z = 0$. When marginalizing the parameter $\Omega_M$, the fitting results are found to be $(w_0, w_z)=(-0.95^{+0.45}_{-0.18}, 0.41^{+0.79}_{-0.96})$. After adding the splitting angle statistic of SGL data, a consistent constraint is obtained $(\Omega_M, w)=(0.298, -0.907)$ and the constraints on time-varying dark energy are further improved to be $(w_0, w_z) = (-0.92^{+0.14}_{-0.10}, 0.35^{+0.47}_{-0.54})$, which indicates that the phantom type models are disfavored.Comment: 24 pages, 9 figures, to be published in JCA

Origins of the Ambient Solar Wind: Implications for Space Weather

The Sun's outer atmosphere is heated to temperatures of millions of degrees, and solar plasma flows out into interplanetary space at supersonic speeds. This paper reviews our current understanding of these interrelated problems: coronal heating and the acceleration of the ambient solar wind. We also discuss where the community stands in its ability to forecast how variations in the solar wind (i.e., fast and slow wind streams) impact the Earth. Although the last few decades have seen significant progress in observations and modeling, we still do not have a complete understanding of the relevant physical processes, nor do we have a quantitatively precise census of which coronal structures contribute to specific types of solar wind. Fast streams are known to be connected to the central regions of large coronal holes. Slow streams, however, appear to come from a wide range of sources, including streamers, pseudostreamers, coronal loops, active regions, and coronal hole boundaries. Complicating our understanding even more is the fact that processes such as turbulence, stream-stream interactions, and Coulomb collisions can make it difficult to unambiguously map a parcel measured at 1 AU back down to its coronal source. We also review recent progress -- in theoretical modeling, observational data analysis, and forecasting techniques that sit at the interface between data and theory -- that gives us hope that the above problems are indeed solvable.Comment: Accepted for publication in Space Science Reviews. Special issue connected with a 2016 ISSI workshop on "The Scientific Foundations of Space Weather." 44 pages, 9 figure

Access to Print in Low‐Income and Middle‐Income Communities: An Ecological Study of Four Neighborhoods

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88026/1/RRQ.36.1.1.pd

Reenacting sensorimotor features of drawing movements from friction sounds

International audienceEven though we generally don't pay attention to the friction sounds produced when we are writing or drawing, these sounds are recordable, and can even evoke the underlying gesture. In this paper, auditory perception of such sounds, and the internal representations they evoke when we listen to them, is considered from the sensorimotor learning point of view. The use of synthesis processes of friction sounds makes it possible to investigate the perceptual influence of each gestures parameter separately. Here, the influence of the velocity profile on the mental representation of the gesture induced by a friction sound was investigated through 3 experiments. The results reveal the perceptual relevance of this parameter, and particularly a specific morphology corresponding to biological movements, the so-called 1/3-power law. The experiments are discussed according to the sensorimotor theory and the invariant taxonomy of the ecological approach

The spiritual organization: critical reflections on the instrumentality of workplace spirituality

Authors' draft of article. Final version published by Routledge in Journal of Management, Spirituality and Religion available online at: http://www.tandf.co.uk/journals/titles/14766086.aspThis paper offers a theoretical contribution to the current debate on workplace spirituality by: (a) providing a selective critical review of scholarship, research and corporate practices which treat workplace spirituality in performative terms, that is, as a resource or means to be manipulated instrumentally and appropriated for economic ends; (b) extending Ezioni’s analysis of complex organizations and proposing a new category, the ‘spiritual organization’, and; (c) positing three alternative positions with respect to workplace spirituality that follow from the preceding critique. The spiritual organization can be taken to represent the development of a trajectory of social technologies that have sought, incrementally, to control the bodies, minds, emotions and souls of employees. Alternatively, it might be employed to conceptualize the way in which employees use the workplace as a site for pursuing their own spiritualities (a reverse instrumentalism). Finally, we consider the possible incommensurability of ‘work organization’ and ‘spirituality’ discourses

Measurement of (anti)deuteron and (anti)proton production in DIS at HERA

The first observation of (anti)deuterons in deep inelastic scattering at HERA has been made with the ZEUS detector at a centre-of-mass energy of 300--318 GeV using an integrated luminosity of 120 pb-1. The measurement was performed in the central rapidity region for transverse momentum per unit of mass in the range 0.3<p_T/M<0.7. The particle rates have been extracted and interpreted in terms of the coalescence model. The (anti)deuteron production yield is smaller than the (anti)proton yield by approximately three orders of magnitude, consistent with the world measurements.Comment: 26 pages, 9 figures, 5 tables, submitted to Nucl. Phys.

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization