Quantitative analysis of mannitol polymorphs: X-ray powder diffractometry—exploring preferred orientation effects

Mannitol is a polymorphic pharmaceutical excipient, which commonly exists in three forms: alpha, beta and delta. Each polymorph has a needle-like morphology, which can give preferred orientation effects when analysed by X-ray powder diffractometry (XRPD) thus providing difficulties for quantitative XRPD assessments. The occurrence of preferred orientation may be demonstrated by sample rotation and the consequent effects on X-ray data can be minimised by reducing the particle size. Using two particle size ranges (less than 125 and 125–500�microns), binary mixtures of beta and delta mannitol were prepared and the delta component was quantified. Samples were assayed in either a static or rotating sampling accessory. Rotation and reducing the particle size range to less than�125 microns halved the limits of detection and quantitation to 1 and 3.6%, respectively. Numerous potential sources of assay errors were investigated; sample packing and mixing errors contributed the greatest source of variation. However, the rotation of samples for both particle size ranges reduced the majority of assay errors examined. This study shows that coupling sample rotation with a particle size reduction minimises preferred orientation effects on assay accuracy, allowing discrimination of two very similar polymorphs at around the 1% level

Determination of the density of the multiple access interference of a CDMA system from its moments

A standard CDMA system is considered and an extension of Pearson's results is used to determine the density function of the interference. The method is shown to work well in some cases, but not so in others. However this approach can be useful in further determining the probability of error of the system with minimal computational requirements.

Random-walk-based characterisation of multiple access interference in a DS/SSMA system

The problem of calculating the probability of error in a DS/SSMA system has been extensively studied for more than two decades. When random sequences are employed some conditioning must be done before the application of the central limit theorem is attempted, leading to a Gaussian distribution. The authors seek to characterise the multiple access interference as a random-walk with a random number of steps, for random and deterministic sequences. Using results from random-walk theory, they model the interference as a K-distributed random variable and use it to calculate the probability of error in the form of a series, for a DS/SSMA system with a coherent correlation receiver and BPSK modulation under Gaussian noise. The asymptotic properties of the proposed distribution agree with other analyses. This is, to the best of the authors' knowledge, the first attempt to propose a non-Gaussian distribution for the interference. The modelling can be extended to consider multipath fading and general modulation

Spatial and temporal patterns in antimicrobial resistance of Salmonella Typhimurium in cattle in England and Wales

Salmonella is the second most commonly reported human foodborne pathogen in England and Wales, and antimicrobial-resistant strains of Salmonella are an increasing problem in both human and veterinary medicine. In this work we used a generalized linear spatial model to estimate the spatial and temporal patterns of antimicrobial resistance in Salmonella Typhimurium in England and Wales. Of the antimicrobials considered we found a common peak in the probability that an S. Typhimurium incident will show resistance to a given antimicrobial in late spring and in mid to late autumn; however, for one of the antimicrobials (streptomycin) there was a sharp drop, over the last 18 months of the period of investigation, in the probability of resistance. We also found a higher probability of resistance in North Wales which is consistent across the antimicrobials considered. This information contributes to our understanding of the epidemiology of antimicrobial resistance in Salmonella.

The dependence of contrail formation on the weather pattern and altitude in the North Atlantic

Aircraft flying through cold ice-supersaturated air produce persistent contrails which contribute to the climate impact of aviation. Here, we demonstrate the importance of the weather situation, together with the route and altitude of the aircraft through this, on estimating contrail coverage. The results have implications for determining the climate impact of contrails as well as potential mitigation strategies. Twenty-one years of re-analysis data are used to produce a climatological assessment of conditions favorable for persistent contrail formation between 200 and 300 hPa over the north Atlantic in winter. The seasonal-mean frequency of cold ice-supersaturated regions is highest near 300 hPa, and decreases with altitude. The frequency of occurrence of ice-supersaturated regions varies with large-scale weather pattern; the most common locations are over Greenland, on the southern side of the jet stream and around the northern edge of high pressure ridges. Assuming aircraft take a great circle route, as opposed to a more realistic time-optimal route, is likely to lead to an error in the estimated contrail coverage, which can exceed 50% for westbound north Atlantic flights. The probability of contrail formation can increase or decrease with height, depending on the weather pattern, indicating that the generic suggestion that flying higher leads to fewer contrails is not robust.

On the quantum mechanical scattering statistics of many particles

The probability of a quantum particle being detected in a given solid angle is determined by the S-matrix. The explanation of this fact in time-dependent scattering theory is often linked to the quantum flux, since the quantum flux integrated against a (detector-) surface and over a time interval can be viewed as the probability that the particle crosses this surface within the given time interval. Regarding many particle scattering, however, this argument is no longer valid, as each particle arrives at the detector at its own random time. While various treatments of this problem can be envisaged, here we present a straightforward Bohmian analysis of many particle potential scattering from which the S-matrix probability emerges in the limit of large distances.

Social networks and occupational choice: the endogenous formation of attitudes and beliefs about tax compliance

The paper analyses the emergence of group-specific attitudes and beliefs about tax compliance when individuals interact in a social network. It develops a model in which taxpayers possess a range of individual characteristics – including attitude to risk, potential for success in self-employment, and the weight attached to the social custom for honesty – and make an occupational choice based on these characteristics. Occupations differ in the possibility for evading tax. The social network determines which taxpayers are linked, and information about auditing and compliance is transmitted at meetings between linked taxpayers. Using agent-based simulations, the analysis demonstrates how attitudes and beliefs endogenously emerge that differ across sub-groups of the population. Compliance behaviour is different across occupational groups, and this is reinforced by the development of group-specific attitudes and beliefs. Taxpayers self-select into occupations according to the degree of risk aversion, the subjective probability of audit is sustained above the objective probability, and the weight attached to the social custom differs across occupations. These factors combine to lead to compliance levels that differ across occupations.

On reliability analysis of multi-categorical forecasts

Reliability analysis of probabilistic forecasts, in particular through the rank histogram or Talagrand diagram, is revisited. Two shortcomings are pointed out: Firstly, a uniform rank histogram is but a necessary condition for reliability. Secondly, if the forecast is assumed to be reliable, an indication is needed how far a histogram is expected to deviate from uniformity merely due to randomness. Concerning the first shortcoming, it is suggested that forecasts be grouped or stratified along suitable criteria, and that reliability is analyzed individually for each forecast stratum. A reliable forecast should have uniform histograms for all individual forecast strata, not only for all forecasts as a whole. As to the second shortcoming, instead of the observed frequencies, the probability of the observed frequency is plotted, providing and indication of the likelihood of the result under the hypothesis that the forecast is reliable. Furthermore, a Goodness-Of-Fit statistic is discussed which is essentially the reliability term of the Ignorance score. The discussed tools are applied to medium range forecasts for 2 m-temperature anomalies at several locations and lead times. The forecasts are stratified along the expected ranked probability score. Those forecasts which feature a high expected score turn out to be particularly unreliable.