No abstract

If a series of air trajectories is drawn from a fixed point at a certain height above the earth's surface, the end-points of the superimposed trajectories, after each has been followed for a time t, will have a standard vector deviation S. The purpose of this paper is to discuss the form of S. One expression is obtained by relating S empirically to the magnitude of the mean vector position [x] of the ends of the trajectories, so that $S = CL |[X|L]|^a,$where L is a certain length and C and a are dimensionless constants; a is found to be about 0·870 and C is nearly proportional to $\surd T$, where T is the total period over which the series of trajectories is initiated.A more satisfying expression for S connects it with the variability of the wind during the priod of initiation of the trajectories, i.e. with the standard vector deviation of wind (ω) which is itself dependent on T. The relationship involves the Lagrangian correlation coefficient r(t) of wind with time along the trajectories. It is found that the variation of S with time t agrees well with that deduced from the exponential formula r(t) = e-αt. Moreover, α, the reciprocal of the characteristic time of the ‘eddies’, is identified with ω2/K where K is the coefficient of eddy viscosity for lateral mixing.

The percentage of obese individuals in the population has increased exponentially over the last decade, making obesity a phenomenon of significant global concern. Individual behaviors, preferences and lifestyle choices are subject to social and environmental influences and social networks have been identified as a key contributor to the global obesity epidemic. Numerous empirical studies have found a relationship between dimensions of social capital, well-being and population health. It is the thesis of this article that social capital in online social networks might be similarly associated. Addressing previously identified gaps in the literature, our conceptual model enables the analysis of the relationships between the structure and content of an individual's online social network, the resulting opportunities and limitations to accessing resources and his or her health-related behaviors and body weight is introduced. Moreover, the model incorporates potential social capital as a special type of social capital in online social networks and uses network-based measures instead of self-reported data. Additionally, literaturebased hypotheses discussing the relationships between the constructs of the model are presented. Establishing profound theoretical groundwork, this article encourages future research crossing the boundaries between information systems, health informatics and sociology. This study concludes by proposing a new Facebook e-health application to collect longitudinal data using the aforementioned conceptual model in order to explore the presented ideas further.

BROOKS, I).SC., c'. 5 . L)lRST, B.A., and N. C.\KKCiTHIiRS, c . 5~ 1 . INTHOI~TCTION FCEE AIKFor the greater part of tho world, data of wind direction and velocity in the free air a r e very scanty or non-existent. In many countries pilot balloon observations have been taken for many years, but the wind roses obtained lrom these are inaccurate and misleading for two reasons: (a) because data are obtained only for days on which the balloon was not hidden by cloud ; and (b) because with increase of height fewer and fewer occasions of strong winds are included owing to the disappearance of the balloon in the dis ta m e . l l i t h radio methods of observation the first of these limitations is completely and the second partially overcome, but as yet the radio wind stations are too few, and have been in operation for too short a time, to describe the general circulation of the atniospherc at great hcights. To collect the necessary information will take many years, but it is thought that in the meantime a n extrapolation can t e effected by the use of thc data at present available. The object of the present paper is t c show that, given the resultant direction and velocity of the wind a t i i point in the free air and sonic measure of the scatter of the individual observations about the resultant, it is practicable to coastruct a wind rose to show the frequency distribution of winds of different directions and velocities which \\.auld be given by a long series of observations. The resultant tlirection and velocity, and the scatter, can be derived from a relatively short series of data with much greater accuracy than the frequencies of observations falling i n individual cells of direction and velocity, which generally give a rather irregular distribution, so that such a reconstruction is in effect a "smoothing" process. It is strictly analogous to the representation of the ideal distribution of a series of, e.g. temperatures, by a frequency curve constructed from the mean and standard deviation o f the series. The quesiion of the estimation of the resultant wind and scatter, when no actual wind observations arc available in the free air, is left to a subsequent paper. 2.'I'IIE TYPE O F FREQVI-A'CY DISTIIIBVTIOS IX A N'VIKD ROS1,:

SUMMARYCorrelation coefficients have been formed between the winds at pairs of points, the correlation being made between components along the line joining the points and also between components at right-angles. The original purpose was the derivation of the effective winds experienced by aircraft. However, certain results are found which appear to throw light on the application of turbulence theory to the large-scale pattern of winds and hence it is thought that the results may be of more general interest.