Regional Importance of Alnus Pollen as an Aeroallergen: A Comparative Study of Alnus Pollen Counts from Worcester (UK) and Poznań (Poland)

Daily average Alnus pollen counts (1996-2005) from Worcester (UK) and Poznań (Poland) were examined with the aim of assessing the regional importance of Alnus pollen as an aeroallergen. The average number of Alnus pollen grains recorded annually at Poznań was more than 2.5 times that of Worcester. Furthermore, daily average Alnus pollen counts exceeded the thresholds of 100, 500 and 1,000 grains/m3 more times at Poznań than Worcester. Skin prick test results (1996-2005) and allergen-specific IgE(asIgE) measurements using the CAP (Pharmacia) system (2002-2005), were supplied by the Allergic Diseases Diagnostic Centre in Poznań. The annual number of positive skin prick tests to Alnus pollen allergens was significantly related (p<0.05) to seasonal variations in the magnitude of the Alnus pollen catch recorded at Poznań (r=0.70). The symptoms of patients with positive skin prick tests to Alnus pollen allergens were: 51% pollinosis, 43% atopic dermatitis, 4% asthma, 1% chronic urticaria and 1% eczema. On a scale of 0-6, 20.5% of patients examined for serum asIgE in relation to Alnus pollen allergens had asIgE measurements in classes 5 and 6. Alnus pollen is generally considered to be mildly allergenic. However, the amount of Alnus pollen released into the atmosphere in places such as Poznań may increase its impact on the population and make it one of the more important aeroallergens present.

Influence of the North Atlantic Oscillation on Grass Pollen Counts in Europe

Relationships between temporal variations in the North Atlantic Oscillation (NAO) and grass pollen counts at 13 sites in Europe, ranging from Córdoba in the South-West and Turku in the North-East, were studied in order to determine spatial differences in the amount of influence exerted by the NAO on the timing and magnitude of grass pollen seasons. There were a number of significant (p<0.05) relationships between the NAO and start dates of the grass pollen season at the 13 pollen-monitoring sites. The strongest associations were generally recorded near to the Atlantic coast. Several significant correlations also existed between winter averages of the NAO and grass pollen season severity. Traditional methods for predicting the start or magnitude of grass pollen seasons have centred on the use of local meteorological observations, but this study has shown the importance of considering large-scale patterns of climate variability like the NAO.

Airborne Olive Pollen Counts are not Representative of 1 Exposure to the Major Olive Allergen Ole e 1

Pollen is routinely monitored, but it is unknown whether pollen counts represent allergen exposure. We therefore simultaneously determined olive pollen and Ole e 1 in ambient air in C"ordoba, Spain, and "Evora, Portugal, using Hirst-type traps for pollen and high-volume cascade impactors for allergen. Pollen from different days released 12-fold different amounts of Ole e 1 per pollen (both locations P < 0.001). Average allergen release from pollen (pollen potency) was much higher in C"ordoba (3.9 pg Ole e 1/pollen) than in "Evora (0.8 pg Ole e 1/pollen, P = 0.004). Indeed, yearly olive pollen counts in C"ordoba were 2.4 times higher than in "Evora, but Ole e 1 concentrations were 7.6 times higher. When modeling the origin of the pollen, >40% of Ole e 1 exposure in "Evora was explained by high-potency pollen originating from the south of Spain. Thus, olive pollen can vary substantially in allergen release, even though they are morphologically identical.

Comparison of Poaceae Pollen Counts Recorded at Sites in Portugal, Spain and the UK

The main aim of this study was to analyse the temporal and spatial variations in grass (Poaceae) pollen counts (2005–2011) recorded in Évora (Portugal), Badajoz (Spain) and Worcester (UK). Weekly average data were examined using nonparametric statistics to compare differences between places. On average, Évora recorded the earliest start dates of the Poaceae pollen seasons and Worcester the latest. The intensity of the Poaceae pollen season varied between sites, with Worcester usually recording the least and Évora the most grass pollen in a season. Mean durations of grass pollen seasons were 77 days in Évora, 78 days in Badajoz and 59 days in Worcester. Overall, longer Poaceae pollen seasons coincided with earlier pollen season start dates. Weekly pollen data, from March to September, from the three pollen-monitoring stations studied were compared. The best fit and most statistically significant correlations were obtained by moving Worcester data backward by 4 weeks (Évora, r = 0.810, p < 0.001) and 5 weeks (Badajoz,r = 0.849, p < 0.001). Weekly data from Worcester therefore followed a similar pattern to that of Badajoz and Évora but at a distance of more than 1,500 km and 4–5 weeks later. The sum of pollen recorded in a season was compared with monthly rainfall between January and May. The strongest positive relationship between season intensity and rainfall was between the annual sum of Poaceae pollen recorded in the season at Badajoz and Évora and total rainfall during January and February. Winter rainfall noticeably affects the intensity of Poaceae pollen seasons in Mediterranean areas, but this was not as important in Worcester.

Behavioral Measures and their Correlation with IPM Iteration Counts on Semi-Definite Programming Problems

We study four measures of problem instance behavior that might account for the observed differences in interior-point method (IPM) iterations when these methods are used to solve semidefinite programming (SDP) problem instances: (i) an aggregate geometry measure related to the primal and dual feasible regions (aspect ratios) and norms of the optimal solutions, (ii) the (Renegar-) condition measure C(d) of the data instance, (iii) a measure of the near-absence of strict complementarity of the optimal solution, and (iv) the level of degeneracy of the optimal solution. We compute these measures for the SDPLIB suite problem instances and measure the correlation between these measures and IPM iteration counts (solved using the software SDPT3) when the measures have finite values. Our conclusions are roughly as follows: the aggregate geometry measure is highly correlated with IPM iterations (CORR = 0.896), and is a very good predictor of IPM iterations, particularly for problem instances with solutions of small norm and aspect ratio. The condition measure C(d) is also correlated with IPM iterations, but less so than the aggregate geometry measure (CORR = 0.630). The near-absence of strict complementarity is weakly correlated with IPM iterations (CORR = 0.423). The level of degeneracy of the optimal solution is essentially uncorrelated with IPM iterations.

Bayesian tools for zero counts in compositional data

The log-ratio methodology makes available powerful tools for analyzing compositional data. Nevertheless, the use of this methodology is only possible for those data sets without null values. Consequently, in those data sets where the zeros are present, a previous treatment becomes necessary. Last advances in the treatment of compositional zeros have been centered especially in the zeros of structural nature and in the rounded zeros. These tools do not contemplate the particular case of count compositional data sets with null values. In this work we deal with \count zeros" and we introduce a treatment based on a mixed Bayesian-multiplicative estimation. We use the Dirichlet probability distribution as a prior and we estimate the posterior probabilities. Then we apply a multiplicative modi¯cation for the non-zero values. We present a case study where this new methodology is applied. Key words: count data, multiplicative replacement, composition, log-ratio analysis

What counts as response and intervention in RTI? : A sociocultural an??lisis

Resumen tomado de la publicaci??n

A Field Evaluation of the Time-of-Detection Method to Estimate Population Size and Density for Aural Avian Point Counts

The time-of-detection method for aural avian point counts is a new method of estimating abundance, allowing for uncertain probability of detection. The method has been specifically designed to allow for variation in singing rates of birds. It involves dividing the time interval of the point count into several subintervals and recording the detection history of the subintervals when each bird sings. The method can be viewed as generating data equivalent to closed capture–recapture information. The method is different from the distance and multiple-observer methods in that it is not required that all the birds sing during the point count. As this method is new and there is some concern as to how well individual birds can be followed, we carried out a field test of the method using simulated known populations of singing birds, using a laptop computer to send signals to audio stations distributed around a point. The system mimics actual aural avian point counts, but also allows us to know the size and spatial distribution of the populations we are sampling. Fifty 8-min point counts (broken into four 2-min intervals) using eight species of birds were simulated. Singing rate of an individual bird of a species was simulated following a Markovian process (singing bouts followed by periods of silence), which we felt was more realistic than a truly random process. The main emphasis of our paper is to compare results from species singing at (high and low) homogenous rates per interval with those singing at (high and low) heterogeneous rates. Population size was estimated accurately for the species simulated, with a high homogeneous probability of singing. Populations of simulated species with lower but homogeneous singing probabilities were somewhat underestimated. Populations of species simulated with heterogeneous singing probabilities were substantially underestimated. Underestimation was caused by both the very low detection probabilities of all distant individuals and by individuals with low singing rates also having very low detection probabilities.

Data assimilation: From photon counts to Earth System forecasts

Data assimilation – the set of techniques whereby information from observing systems and models is combined optimally – is rapidly becoming prominent in endeavours to exploit Earth Observation for Earth sciences, including climate prediction. This paper explains the broad principles of data assimilation, outlining different approaches (optimal interpolation, three-dimensional and four-dimensional variational methods, the Kalman Filter), together with the approximations that are often necessary to make them practicable. After pointing out a variety of benefits of data assimilation, the paper then outlines some practical applications of the exploitation of Earth Observation by data assimilation in the areas of operational oceanography, chemical weather forecasting and carbon cycle modelling. Finally, some challenges for the future are noted.

A novel variant on chromosome 7q22.3 associated with mean platelet volume, counts, and function

Mean platelet volume (MPV) and platelet count (PLT) are highly heritable and tightly regulated traits. We performed a genome-wide association study for MPV and identified one SNP, rs342293, as having highly significant and reproducible association with MPV (per-G allele effect 0.016 +/- 0.001 log fL; P < 1.08 x 10(-24)) and PLT (per-G effect -4.55 +/- 0.80 10(9)/L; P < 7.19 x 10(-8)) in 8586 healthy subjects. Whole-genome expression analysis in the 1-MB region showed a significant association with platelet transcript levels for PIK3CG (n = 35; P = .047). The G allele at rs342293 was also associated with decreased binding of annexin V to platelets activated with collagen-related peptide (n = 84; P = .003). The region 7q22.3 identifies the first QTL influencing platelet volume, counts, and function in healthy subjects. Notably, the association signal maps to a chromosome region implicated in myeloid malignancies, indicating this site as an important regulatory site for hematopoiesis. The identification of loci regulating MPV by this and other studies will increase our insight in the processes of megakaryopoiesis and proplatelet formation, and it may aid the identification of genes that are somatically mutated in essential thrombocytosis. (Blood. 2009; 113: 3831-3837)

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.

Therapist characteristics and their effect on training outcomes: what counts?

Background: Evidence exists for a relationship between individual characteristics and both job and training performance; however relationships may not be generalizable. Little is known about the impact of therapist characteristics on performance in postgraduate therapist training programmes. Aims: The aim of this study was to investigate associations between the grades of trainee Low-Intensity and High-Intensity cognitive behavioural therapists and individual characteristics. Method: Trainee Low-Intensity (n=81) and High-Intensity (n=59) therapists completed measures of personality and cognitive ability; demographic and course grade data for participants were collected. Results: Degree classification emerged as the only variable to be significantly associated with performance across assessments and courses. Higher undergraduate degree classifications were associated with superior academic and clinical performance. Agreeableness was the only dimension of personality to be associated (positively) with clinical skill. Age was weakly and negatively associated with performance. Conclusions: Relationships between individual characteristics and training outcomes are complex and may be context specific. These results could have important implications for the selection and development of therapists for Low or High-Intensity cognitive behavioural therapy (CBT) training.

Effect of somatic cell counts on lipolysis, proteolysis and apparent viscosity of UHT milk during storage

In this work, lipolysis, proteolysis and viscosity of ultra-high temperature (UHT) milk containing different somatic cell counts (SCC) were investigated. UHT milks were analysed on days 8, 30, 60, 90 and 120 of storage. Lipolysis as measured by free fatty acids increase, casein degradation and viscosity of UHT milk were not affected by SCC but increased during storage. A negative relationship was observed between SCC and casein as a percentage of true protein on the 120th day of storage, hence indicating that high SCC increases the proteolysis of UHT milk by the end of its shelf life.