Birch pollen rupture and the release of aerosols of respirable allergens

Backgound Birch pollen allergens have been implicated as asthma triggers; however, pollen grains are too large to reach the lower airways where asthmatic reactions occur. Respirable-sized particles containing birch pollen allergens have been detected in air filters, especially after rainfall but the source of these particles has remained speculative.

Objective To determine the processes by which birch pollen allergens become airborne particles of respirable size with the potential to contribute to airways inflammation.

Methods Branches with attached male catkins were harvested and placed in a controlled emission chamber. Filtered dry air was passed through the chamber until the anthers opened, then they were humidified for 5 h and air-dried again. Flowers were disturbed by wind generated from a small electric fan. Released particles were counted, measured and collected for immuno-labelling and high-resolution microscopy.

Results Birch pollen remains on the dehisced anther and can rupture in high humidity and moisture. Fresh pollen takes as long as 3 h to rupture in water. Drying winds released an aerosol of particles from catkins. These were fragments of pollen cytoplasm that ranged in size from 30 nm to 4 μm and contained Bet v 1 allergens.

Conclusion When highly allergenic birch trees are flowering and exposed to moisture followed by drying winds they can produce particulate aerosols containing pollen allergens. These particles are small enough to deposit in the peripheral airways and have the potential to induce an inflammatory response.

Involvement of rootstocks and their hydraulic conductance in the drought resistance of grafted rubber trees

Improving drought resistance of rubber trees has become a pressing issue with the extension of rubber plantations and the prevalence of seasonal drought. Root system is vital to water and nutrients uptake of all plants, therefore, rootstocks could play decisive roles in drought resistance of grafted rubber trees on a specific scion clone. To investigate the responses of different clone rootstocks and their grafted trees to water stress and find applicable methods for selecting drought resistant rootstocks, seven related parameters and root hydraulic properties of both seeds originated and grafted saplings of PB86, PR107, RRIM600 and GT1 were measured to assess their drought resistance. It was shown that the rootstock drought resistance and root hydraulic conductance may improve the drought resistance of the grafted rubber trees. Among the four clone rootstocks, GT1, which demonstrated more resistant to drought and higher root hydraulic conductance, was comparatively resistant to drought both for the seed propagation seedlings and grafted saplings. In addition, studies on the grafted saplings with different root hydraulic conductance further validated the possibility of selecting drought resistant rootstocks on the basis of rootstock hydraulic conductance using a high-pressure flow meter.

Extracting common subtrees from decision trees

This paper explores an efficient technique for the extraction of common subtrees in decision trees. The method is based on a Suffix Tree string matching process and the algorithm is applied to the problem of finding common decision rules in path planning.

Video indexing and similarity retrieval by largest common subgraph detection using decision trees

While the largest common subgraph (LCSG) between a query and a database of models can provide an elegant and intuitive measure of similarity for many applications, it is computationally expensive to compute. Recently developed algorithms for subgraph isomorphism detection take advantage of prior knowledge of a database of models to improve the speed of on-line matching. This paper presents a new algorithm based on similar principles to solve the largest common subgraph problem. The new algorithm significantly reduces the computational complexity of detection of the LCSG between a known database of models, and a query given on-line.

Bayesian networks and decision trees in the diagnosis of female urinary incontinence

This study compares the effectiveness of Bayesian networks versus Decision Trees in modeling the Integral Theory of Female Urinary Incontinence diagnostic algorithm. Bayesian networks and Decision Trees were developed and trained using data from 58 adult women presenting with urinary incontinence symptoms. A Bayesian Network was developed in collaboration with an expert specialist who regularly utilizes a non-automated diagnostic algorithm in clinical practice. The original Bayesian network was later refined using a more connected approach. Diagnoses determined from all automated approaches were compared with the diagnoses of a single human expert. In most cases, Bayesian networks were found to be at least as accurate as the Decision Tree approach. The refined Connected Bayesian Network was found to be more accurate than the Original Bayesian Network accurately discriminated between diagnoses despite the small sample size. In contrast, the Connected and Decision Tree approaches were less able to discriminate between diagnoses. The Original Bayesian Network was found to provide an excellent basis for graphically communicating the correlation between symptoms and laxity defects in a given anatomical zone. Performance measures in both networks indicate that Bayesian networks could provide a potentially useful tool in the management of female pelvic floor dysfunction. Before the technique can be utilized in practice, well-established learning algorithms should be applied to improve network structure. A larger training data set should also improve network accuracy, sensitivity, and specificity.

A comparative analysis of decision trees vis-à-vis other computational data mining techniques in automotive insurance fraud detection

The development and application of computational data mining techniques in financial fraud detection and business failure prediction has become a popular cross-disciplinary research area in recent times involving financial economists, forensic accountants and computational modellers. Some of the computational techniques popularly used in the context of - financial fraud detection and business failure prediction can also be effectively applied in the detection of fraudulent insurance claims and therefore, can be of immense practical value to the insurance industry. We provide a comparative analysis of prediction performance of a battery of data mining techniques using real-life automotive insurance fraud data. While the data we have used in our paper is US-based, the computational techniques we have tested can be adapted and generally applied to detect similar insurance frauds in other countries as well where an organized automotive insurance industry exists.

Genetic correlation between resting metabolic rate and exploratory behaviour in deer mice (Peromyscus maniculatus)

According to the ‘pace-of-life’ syndrome hypothesis, differences in resting metabolic rate (RMR) should be genetically associated with exploratory behaviour. A large number of studies reported significant heritability for both RMR and exploratory behaviour, but the genetic correlation between the two has yet to be documented. We used a quantitative genetic approach to decompose the phenotypic (co)variance of several metabolic and behavioural measures into components of additive genetic, common environment and permanent environment variance in captive deer mice. We found significant additive genetic variance for two mass-independent metabolic measures (RMR and the average metabolic rate throughout the respirometry run) and two behavioural measures (time spent in centre and distance moved in a novel environment). We also detected positive additive genetic correlation between mass-independent RMR and distance moved (rA = 0.78 ± 0.23). Our results suggest that RMR and exploratory behaviour are functionally integrated traits in deer mice, providing empirical support for one of the connections within the pace-of-life syndrome hypothesis.

Two trees: Australian artists' books to Afghanistan and back

Two Trees documents an artists' books collaboration between 14 Australian women artists and women in Afghanistan who were learning literacy. The collaboration resulted in 36 concertina books of images, withDari and Pashto hand written texts.The books are held in the State Library of Queensland's artists' books collection. Two Trees includes includes an introduction by Barbara Kameniar, and texts by Malalai Joya, Gali Weiss, Matthias Thomczak and Latifa Ahmady.