Quantitative analysis of mannitol polymorphs: FT-Raman spectroscopy

Mannitol is a polymorphic excipient which is usually used in pharmaceutical products as the beta form, although other polymorphs (alpha and delta) are common contaminants. Binary mixtures containing beta and delta mannitol were prepared to quantify the concentration of the beta form using FT-Raman spectroscopy. Spectral regions characteristic of each form were selected and peak intensity ratios of beta peaks to delta peaks were calculated. Using these ratios, a correlation curve was established which was then validated by analysing further samples of known composition. The results indicate that levels down to 2% beta could be quantified using this novel, non-destructive approach. Potential errors associated with quantitative studies using FT-Raman spectroscopy were also researched. The principal source of variability arose from inhomogeneities on mixing of the samples; a significant reduction of these errors was observed by reducing and controlling the particle size range. The results show that FT-Raman spectroscopy can be used to rapidly and accurately quantitate polymorphic mixtures.

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

Physical interpretation of the spectral radiative signature in the transition zone between cloud-free and cloudy regions

One-second-resolution zenith radiance measure- ments from the Atmospheric Radiation Measurement pro- gram’s new shortwave spectrometer (SWS) provide a unique opportunity to analyze the transition zone between cloudy and cloud-free air, which has considerable bearing on the aerosol indirect effect. In the transition zone, we find a re- markable linear relationship between the sum and difference of radiances at 870 and 1640 nm wavelengths. The intercept of the relationship is determined primarily by aerosol prop- erties, and the slope by cloud properties. We then show that this linearity can be predicted from simple theoretical con- siderations and furthermore that it supports the hypothesis of inhomogeneous mixing, whereby optical depth increases as a cloud is approached but the effective drop size remains un- changed.

Quantitative precipitation estimation over ocean using Bayesian approach from microwave observations during the typhoon season

We have developed a new Bayesian approach to retrieve oceanic rain rate from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), with an emphasis on typhoon cases in the West Pacific. Retrieved rain rates are validated with measurements of rain gauges located on Japanese islands. To demonstrate improvement, retrievals are also compared with those from the TRMM/Precipitation Radar (PR), the Goddard Profiling Algorithm (GPROF), and a multi-channel linear regression statistical method (MLRS). We have found that qualitatively, all methods retrieved similar horizontal distributions in terms of locations of eyes and rain bands of typhoons. Quantitatively, our new Bayesian retrievals have the best linearity and the smallest root mean square (RMS) error against rain gauge data for 16 typhoon overpasses in 2004. The correlation coefficient and RMS of our retrievals are 0.95 and ~2 mm hr-1, respectively. In particular, at heavy rain rates, our Bayesian retrievals outperform those retrieved from GPROF and MLRS. Overall, the new Bayesian approach accurately retrieves surface rain rate for typhoon cases. Accurate rain rate estimates from this method can be assimilated in models to improve forecast and prevent potential damages in Taiwan during typhoon seasons.

The socioeconomics of food crop production and climate change vulnerability: a global scale quantitative analysis of how grain crops are sensitive to drought

Many studies warn that climate change may undermine global food security. Much work on this topic focuses on modelling crop-weather interactions but these models do not generally account for the ways in which socio-economic factors influence how harvests are affected by weather. To address this gap, this paper uses a quantitative harvest vulnerability index based on annual soil moisture and grain production data as the dependent variables in a Linear Mixed Effects model with national scale socio-economic data as independent variables for the period 1990-2005. Results show that rice, wheat and maize production in middle income countries were especially vulnerable to droughts. By contrast, harvests in countries with higher investments in agriculture (e.g higher amounts of fertilizer use) were less vulnerable to drought. In terms of differences between the world's major grain crops, factors that made rice and wheat crops vulnerable to drought were quite consistent, whilst those of maize crops varied considerably depending on the type of region. This is likely due to the fact that maize is produced under very different conditions worldwide. One recommendation for reducing drought vulnerability risks is coordinated development and adaptation policies, including institutional support that enables farmers to take proactive action.

Evaluation and comparison of SYBR Green I Real-Time PCR and TaqMan Real-Time PCR methods for quantitative assay of Listeria monocytogenes in nutrient broth and milk

Specific traditional plate count method and real-time PCR systems based on SYBR Green I and TaqMan technologies using a specific primer pair and probe for amplification of iap-gene were used for quantitative assay of Listeria monocytogenes in seven decimal serial dilution series of nutrient broth and milk samples containing 1.58 to 1.58×107 cfu /ml and the real-time PCR methods were compared with the plate count method with respect to accuracy and sensitivity. In this study, the plate count method was performed using surface-plating of 0.1 ml of each sample on Palcam Agar. The lowest detectable level for this method was 1.58×10 cfu/ml for both nutrient broth and milk samples. Using purified DNA as a template for generation of standard curves, as few as four copies of the iap-gene could be detected per reaction with both real-time PCR assays, indicating that they were highly sensitive. When these real-time PCR assays were applied to quantification of L. monocytogenes in decimal serial dilution series of nutrient broth and milk samples, 3.16×10 to 3.16×105 copies per reaction (equals to 1.58×103 to 1.58×107 cfu/ml L. monocytogenes) were detectable. As logarithmic cycles, for Plate Count and both molecular assays, the quantitative results of the detectable steps were similar to the inoculation levels.

Impact of duration thresholds on Atlantic tropical cyclone counts*

Records of Atlantic basin tropical cyclones (TCs) since the late nineteenth century indicate a very large upward trend in storm frequency. This increase in documented TCs has been previously interpreted as resulting from anthropogenic climate change. However, improvements in observing and recording practices provide an alternative interpretation for these changes: recent studies suggest that the number of potentially missed TCs is sufficient to explain a large part of the recorded increase in TC counts. This study explores the influence of another factor—TC duration—on observed changes in TC frequency, using a widely used Atlantic hurricane database (HURDAT). It is found that the occurrence of short-lived storms (duration of 2 days or less) in the database has increased dramatically, from less than one per year in the late nineteenth–early twentieth century to about five per year since about 2000, while medium- to long-lived storms have increased little, if at all. Thus, the previously documented increase in total TC frequency since the late nineteenth century in the database is primarily due to an increase in very short-lived TCs. The authors also undertake a sampling study based upon the distribution of ship observations, which provides quantitative estimates of the frequency of missed TCs, focusing just on the moderate to long-lived systems with durations exceeding 2 days in the raw HURDAT. Upon adding the estimated numbers of missed TCs, the time series of moderate to long-lived Atlantic TCs show substantial multidecadal variability, but neither time series exhibits a significant trend since the late nineteenth century, with a nominal decrease in the adjusted time series. Thus, to understand the source of the century-scale increase in Atlantic TC counts in HURDAT, one must explain the relatively monotonic increase in very short-duration storms since the late nineteenth century. While it is possible that the recorded increase in short-duration TCs represents a real climate signal, the authors consider that it is more plausible that the increase arises primarily from improvements in the quantity and quality of observations, along with enhanced interpretation techniques. These have allowed National Hurricane Center forecasters to better monitor and detect initial TC formation, and thus incorporate increasing numbers of very short-lived systems into the TC database.

Biased interpretation in perfectionism and its modification

Perfectionism is a transdiagnostic construct associated with a range of diagnoses, including depression, eating disorders and obsessive compulsive disorder. Treatments that directly target perfectionist cognitions have been shown to successfully reduce associated pathologies. However, the way in which they do this is not clear. We set out to assess the role of one candidate mechanism of action, namely the cognitive process of interpretation of ambiguity. In one experiment we looked for associations between biased interpretation and perfectionism. In a second, we manipulated interpretations, thereby providing a strong test of their aetiological significance. Results from the first experiment confirmed the presence of biased interpretation in perfectionism and demonstrated that these are highly specific to perfection relevant information, rather than reflecting general negativity. The second experiment succeeded in manipulating these perfection relevant interpretations and demonstrated that one consequence of doing so is a change in perfectionist behaviour. Together, these data experimentally demonstrate that biased interpretation of perfection relevant ambiguity contributes to the maintenance of perfectionism, but that it is also possible to reverse this. Clinical implications include the identification of one likely mechanism of therapeutic change within existing treatments, as well as identification of an appropriate evidence based focus for future treatment development. Targeting underlying functional mechanisms, such as biased interpretation, has the potential to offer transdiagnostic benefits.

A design of evaluation method for SaaS in cloud computing

Purpose: This paper aims to design an evaluation method that enables an organization to assess its current IT landscape and provide readiness assessment prior to Software as a Service (SaaS) adoption. Design/methodology/approach: The research employs a mixed of quantitative and qualitative approaches for conducting an IT application assessment. Quantitative data such as end user’s feedback on the IT applications contribute to the technical impact on efficiency and productivity. Qualitative data such as business domain, business services and IT application cost drivers are used to determine the business value of the IT applications in an organization. Findings: The assessment of IT applications leads to decisions on suitability of each IT application that can be migrated to cloud environment. Research limitations/implications: The evaluation of how a particular IT application impacts on a business service is done based on the logical interpretation. Data mining method is suggested in order to derive the patterns of the IT application capabilities. Practical implications: This method has been applied in a local council in UK. This helps the council to decide the future status of the IT applications for cost saving purpose.

Introduction and the problems of weather interpretation

Numerical forecasts of the atmosphere based on the fundamental dynamical and thermodynamical equations have now been carried for almost 30 years. The very first models which were used were drastic simplifications of the governing equations and permitting only the prediction of the geostrophic wind in the middle of the troposphere based on the conservation of absolute vorticity. Since then we have seen a remarkable development in models predicting the large-scale synoptic flow. Verification carried out at NMC Washington indicates an improvement of about 40% in 24h forecasts for the 500mb geopotential since the end of the 1950’s. The most advanced models of today use the equations of motion in their more original form (i.e. primitive equations) which are better suited to predicting the atmosphere at low latitudes as well as small scale systems. The model which we have developed at the Centre, for instance, will be able to predict weather systems from a scale of 500-1000 km and a vertical extension of a few hundred millibars up to global weather systems extending through the whole depth of the atmosphere. With a grid resolution of 1.5 and 15 vertical levels and covering the whole globe it is possible to describe rather accurately the thermodynamical processes associated with cyclone development. It is further possible to incorporate sub-grid-scale processes such as radiation, exchange of sensible heat, release of latent heat etc. in order to predict the development of new weather systems and the decay of old ones. Later in this introduction I will exemplify this by showing some results of forecasts by the Centre’s model.

The world at one's fingertips: interactive interpretation of environmental data

This chapter introduces the latest practices and technologies in the interactive interpretation of environmental data. With environmental data becoming ever larger, more diverse and more complex, there is a need for a new generation of tools that provides new capabilities over and above those of the standard workhorses of science. These new tools aid the scientist in discovering interesting new features (and also problems) in large datasets by allowing the data to be explored interactively using simple, intuitive graphical tools. In this way, new discoveries are made that are commonly missed by automated batch data processing. This chapter discusses the characteristics of environmental science data, common current practice in data analysis and the supporting tools and infrastructure. New approaches are introduced and illustrated from the points of view of both the end user and the underlying technology. We conclude by speculating as to future developments in the field and what must be achieved to fulfil this vision.

Interpretation and expectation in childhood anxiety disorders: age effects and social specificity

Theory and treatment for childhood anxiety disorders typically implicates children’s negative cognitions, yet little is known about the characteristics of thinking styles of clinically anxious children. In particular, it is unclear whether differences in thinking styles between children with anxiety disorders and non-anxious children vary as a function of child age, whether particular cognitive distortions are associated with childhood anxiety disorders at different child ages, and whether cognitive content is disorder-specific. The current study addressed these questions among 120 7 - 12 year old children (53% female) who met diagnostic criteria for social anxiety disorder, other anxiety disorder, or who were not currently anxious. Contrary to expectations, threat interpretation was not inflated amongst anxious compared to non-anxious children at any age, although older (10 - 12 year old) anxious children did differ from non-anxious children on measures of perceived coping. The notion of cognitive-content specificity was not supported across the age-range. The findings challenge current treatment models of childhood anxiety, and suggest that a focus on changing anxious children’s cognitions is not warranted in mid-childhood, and in late childhood cognitive approaches may be better focussed on promoting children’s perceptions of control rather than challenging threat interpretations.

Quantitative genetic divergence and standing genetic (co)variance in thermal reaction norms along latitude

Although the potential to adapt to warmer climate is constrained by genetic trade-offs, our understanding of how selection and mutation shape genetic (co)variances in thermal reaction norms is poor. Using 71 isofemale lines of the fly Sepsis punctum, originating from northern, central, and southern European climates, we tested for divergence in juvenile development rate across latitude at five experimental temperatures. To investigate effects of evolutionary history in different climates on standing genetic variation in reaction norms, we further compared genetic (co)variances between regions. Flies were reared on either high or low food resources to explore the role of energy acquisition in determining genetic trade-offs between different temperatures. Although the latter had only weak effects on the strength and sign of genetic correlations, genetic architecture differed significantly between climatic regions, implying that evolution of reaction norms proceeds via different trajectories at high latitude versus low latitude in this system. Accordingly, regional genetic architecture was correlated to region-specific differentiation. Moreover, hot development temperatures were associated with low genetic variance and stronger genetic correlations compared to cooler temperatures. We discuss the evolutionary potential of thermal reaction norms in light of their underlying genetic architectures, evolutionary histories, and the materialization of trade-offs in natural environments.