Prevalence and risk factors of childhood allergic diseases in eight metropolitan cities in China: A multicenter study

Background Several studies conducted during the past two decades suggested increasing trend of childhood allergic diseases in China. However, few studies have provided detailed description of geographic variation and explored risk factors of these diseases. This study investigated the pattern and risk factors of asthma, allergic rhinitis and eczema in eight metropolitan cities in China. Methods We conducted a cross-sectional survey during November-December 2005 in eight metropolitan cities in China. A total of 23791 children aged 6-13 years participated in this survey. Questions from the standard questionnaire of the International Study of Asthma and Allergies in Children (ISAAC) were used to examine the pattern of current asthma, allergic rhinitis and eczema. Logistic regression analyses were performed to assess the risk factors for childhood allergies. Results The average prevalence of childhood asthma, allergic rhinitis and eczema across the eight cities was 3∙3% (95% Confidence interval (CI): 3∙1%, 3∙6%), 9∙8% (95% CI: 9∙4%, 10∙2%) and 5∙5% (95% CI: 5∙2%, 5∙8%), respectively. Factors related to lifestyle, mental health and socio-economic status were found to be associated with the prevalence of childhood allergies. These risk factors were unevenly distributed across cities and disproportionately affected the local prevalence. Conclusions There was apparent geographic variation of childhood allergies in China. Socio-environmental factors had strong impacts on the prevalence of childhood allergies; but these impacts differed across regions. Thus public health policies should specifically target at the local risk factors for each individual area.

Workflow resource pattern modelling and visualization

Workflow patterns have been recognized as the theoretical basis to modeling recurring problems in workflow systems. A form of workflow patterns, known as the resource patterns, characterise the behaviour of resources in workflow systems. Despite the fact that many resource patterns have been discovered, people still preclude them from many workflow system implementations. One of reasons could be obscurityin the behaviour of and interaction between resources and a workflow management system. Thus, we provide a modelling and visualization approach for the resource patterns, enabling a resource behaviour modeller to intuitively see the specific resource patterns involved in the lifecycle of a workitem. We believe this research can be extended to benefit not only workflow modelling, but also other applications, such as model validation, human resource behaviour modelling, and workflow model visualization.

Extracting deck trend to plan descent trajectory for safe landing of UAVs

This paper outlines a feasible scheme to extract deck trend when a rotary-wing unmanned aerial vehicle (RUAV)approaches an oscillating deck. An extended Kalman filter (EKF) is de- veloped to fuse measurements from multiple sensors for effective estimation of the unknown deck heave motion. Also, a recursive Prony Analysis (PA) procedure is proposed to implement online curve-fitting of the estimated heave mo- tion. The proposed PA constructs an appropriate model with parameters identified using the forgetting factor recursive least square (FFRLS)method. The deck trend is then extracted by separating dominant modes. Performance of the proposed procedure is evaluated using real ship motion data, and simulation results justify the suitability of the proposed method into safe landing of RUAVs operating in a maritime environment.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Natural convection of nanofluids in open rectangular cavity

An investigation of the effect of nano particles on natural convection of water based nanofluids contained in an open rectangular cavity is carried out numerically. The flow pattern and heat transfer characteristics are studied for different values of volume fraction in the range 0   0.2 , Rayleigh number in the range 9 1 Ra 10 and the nano particles with different thermo physical properties. It was found that for low Rayleigh numbers, heat transfer exhibits a decreasing trend for increasing values of volume fraction of oxide nanofluids, whereas for higher values of Rayleigh numbers, an increasing trend of heat transfer was observed due to increase in the volume fraction of nanofluids.

Retrieving information from microblog using pattern mining and relevance feedback

Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.

Temporal trend of organochlorine pesticides in Australia

Persistent, lipophilic organochlorine pesticides (OCPs) such as dichlorodiphenyltrichloroethane (DDT), hexachlorocyclohexanes (HCHs), dieldrin, chlordanes, hexachlorobenzene (HCB) and mirex are known to accumulate in human samples [1, 2]. Persistent OCPs are among the chemicals that are covered under the Stockholm Convention on persistent organic pollutants [3]. Exceptions to this include relatively less lipophillic compounds like HCH (KOW<10^5). In Australia, OCPs such as DDT and HCHs were introduced in the 1940s. This followed a period of widespread use until the 1970s when recognition of risks related to OCPs resulted in reduced use and their ultimate ban in the 1980s. Mirex, however, remained in very restricted use in Northern Australia for treatment of one species of termites (the Giant Termite (Mastotermes darwinensis)) but this use was phased out in 2007.

Cause of Death, Trend and Disease Burden in Shandong Province, China : the Third Retrospective Sampling Survey of Cause of Death Report

This book describes the mortality for all causes of death and the trend in major causes of death since 1970s in Shandong Province, China.

Scoring-thresholding pattern based text classifier

A big challenge for classification on text is the noisy of text data. It makes classification quality low. Many classification process can be divided into two sequential steps scoring and threshold setting (thresholding). Therefore to deal with noisy data problem, it is important to describe positive feature effectively scoring and to set a suitable threshold. Most existing text classifiers do not concentrate on these two jobs. In this paper, we propose a novel text classifier with pattern-based scoring that describe positive feature effectively, followed by threshold setting. The thresholding is based on score of training set, make it is simple to implement in other scoring methods. Experiment shows that our pattern-based classifier is promising.

Redefining and leading the academic discipline in Australian universities

Disciplines have emerged as an alternative administrative structure to departments or schools in Australian universities. We presently investigate the pattern of discipline use and by way of case study examine a role for distributed leadership in discipline management. Over forty per cent of Australian universities currently employ disciplines, especially within faculties of sciences, engineering and medicine. No trend is observed according to institutional age, state, or historical origins. Effective planning, retention of corporate knowledge and good communication are important during the transition period. Moreover, it is vital that professional staff continue to work closely alongside academics as extended members of the discipline. Distributed leadership encourages this interaction. The duties of a discipline leader can be similar to those faced by a head of department. Universities should therefore establish clear policies, position descriptions and appropriate remuneration packages in order to recruit, train and retain staff within this emerging academic management role.

A pattern based two-stage text classifier

In a classification problem typically we face two challenging issues, the diverse characteristic of negative documents and sometimes a lot of negative documents that are closed to positive documents. Therefore, it is hard for a single classifier to clearly classify incoming documents into classes. This paper proposes a novel gradual problem solving to create a two-stage classifier. The first stage identifies reliable negatives (negative documents with weak positive characteristics). It concentrates on minimizing the number of false negative documents (recall-oriented). We use Rocchio, an existing recall based classifier, for this stage. The second stage is a precision-oriented “fine tuning”, concentrates on minimizing the number of false positive documents by applying pattern (a statistical phrase) mining techniques. In this stage a pattern-based scoring is followed by threshold setting (thresholding). Experiment shows that our statistical phrase based two-stage classifier is promising.

Corporate Social Responsibility Implementation in the EU and USA : The Trend and the Way Forward

The core principles of CSR are being integrated into the core policy objectives of different economies and global companies and are also moving beyond their individual business initiatives. This integration can be seen from individual states’ perspectives; states are also accepting these issues in their socio-economic strategies and thus are establishing these issues within national economies. Given this background, this chapter explicates the trends in implementing CSR principles in the EU and USA. It demonstrates that companies in the developed countries use a mix of different strategies to incorporate CSR principles in their self-regulatory mechanisms. Strategies based on legal regulation are not foremost in this mix; rather, in these countries regulation-based strategy is meant to assist the non-legal drivers of CSR.

Metabolite profiling and pathway analysis of acute hepatitis rats by UPLC-ESI MS combined with pattern recognition methods

BACKGROUND & AIMS Metabolomics is comprehensive analysis of low-molecular-weight endogenous metabolites in a biological sample. It could enable mapping of perturbations of early biochemical changes in diseases and hence provide an opportunity to develop predictive biomarkers that could provide valuable insights into the mechanisms of diseases. The aim of this study was to elucidate the changes in endogenous metabolites and to phenotype the metabolic profiling of d-galactosamine (GalN)-inducing acute hepatitis in rats by UPLC-ESI MS. METHODS The systemic biochemical actions of GalN administration (ip, 400 mg/kg) have been investigated in male wistar rats using conventional clinical chemistry, liver histopathology and metabolomic analysis of UPLC- ESI MS of urine. The urine was collected predose (-24 to 0 h) and 0-24, 24-48, 48-72, 72-96 h post-dose. Mass spectrometry of the urine was analysed visually and via conjunction with multivariate data analysis. RESULTS Results demonstrated that there was a time-dependent biochemical effect of GalN dosed on the levels of a range of low-molecular-weight metabolites in urine, which was correlated with developing phase of the GalN-inducing acute hepatitis. Urinary excretion of beta-hydroxybutanoic acid and citric acid was decreased following GalN dosing, whereas that of glycocholic acid, indole-3-acetic acid, sphinganine, n-acetyl-l-phenylalanine, cholic acid and creatinine excretion was increased, which suggests that several key metabolic pathways such as energy metabolism, lipid metabolism and amino acid metabolism were perturbed by GalN. CONCLUSION This metabolomic investigation demonstrates that this robust non-invasive tool offers insight into the metabolic states of diseases.

Semaphorin–plexin signalling genes associated with human breast tumourigenesis

Introduction Gene expression profiling has enabled us to demonstrate the heterogeneity of breast cancers. The potential of a tumour to grow and metastasise is partly dependant on its ability to initiate angiogenesis or growth and remodelling of new blood vessels, usually from a pre-existing vascular network, to ensure delivery of oxygen, nutrients, and growth factors to rapidly dividing transformed cells along with access to the systemic circulation. Cell–cell signalling of semaphorin ligands through interaction with their plexin receptors is important for the homeostasis and morphogenesis of many tissues and has been widely studied for a role in neural connectivity, cancer, cell migration and immune responses. This study investigated the role of four semaphorin/plexin signalling genes in human breast cancers in vivo and in vitro. Materials and methods mRNA was extracted from formalin fixed paraffin embedded archival breast invasive ductal carcinoma tissue samples of progressive grades (grades I–III) and compared to tissue from benign tumours. Gene expression profiles were determined by microarray using the Affymetrix GeneChip® Human Genome U133 Plus 2.0 Arrays and validated by Q-PCR using a Corbett RotorGene 6000. Following validation, the gene expression profile of the identified targets was correlated with those of the human breast cancer cell lines MCF-7 and MDA-MD-231. Results The array data revealed that 888 genes were found to be significantly (p ≤ 0.05) differentially expressed between grades I and II tumours and 563 genes between grade III and benign tumours. From these genes, we identified four genes involved in semaphorin–plexin signalling including SEMA4D which has previously been identified as being involved in increased angiogenesis in breast cancers, and three other genes, SEMA4F, PLXNA2 and PLXNA3, which in the literature were associated with tumourigenesis, but not directly in breast tumourigenesis. The microarray analysis revealed that SEMA4D was significantly (P = 0.0347) down-regulated in the grade III tumours compared to benign tumours; SEMA4F, was significantly (P = 0.0159) down-regulated between grades I and II tumours; PLXNA2 was significantly (P = 0.036) down-regulated between grade III and benign tumours and PLXNA3 significantly (P = 0.042) up-regulated between grades I and II tumours. Gene expression of SEMA4D was validated using Q-PCR, demonstrating the same expression profile in both data sets. When the sample set was increased to incorporate more cases, SEMA4D continued to follow the same expression profile, including statistical significance for the differences observed and small standard deviations. In vitro the same pattern was present where expression for SEMA4D was significantly higher in MDA-MB-231 cells when compared to MCF-7 cells. The expression of SEMA4F, PLXNA2 and PLXNA3 could not be validated using Q-PCR, however in vitro analysis of these three genes revealed that both SEMA4F and PLXNA3 followed the microarray trend in expression, although they did not reach significance. In contrast, PLXNA2 demonstrated statistical significance and was in concordance with the literature. Discussion We, and others, have proposed SEMA4D to be a gene with a potentially protective effect in benign tumours that contributes to tumour growth and metastatic suppression. Previous data supports a role for SEMA4F as a tumour suppressor in the peripheral nervous system but our data seems to indicate that the gene is involved in tumour progression in breast cancer. Our in vitro analysis of PLXNA2 revealed that the gene has higher expression in more aggressive breast cancer cell types. Finally, our in vitro analysis on PLXNA3 also suggest that this gene may have some form of growth suppressive role in breast cancer, in addition to a similar role for the gene previously reported in ovarian cancer. From the data obtained in this study, SEMA4D may have a role in more aggressive and potentially metastatic breast tumours. Conclusions Semaphorins and their receptors, the plexins, have been implicated in numerous aspects of neural development, however their expression in many other epithelial tissues suggests that the semaphorin–plexin signalling system also contributes to blood vessel growth and development. These findings warrant further investigation of the role of semaphorins and plexins and their role in normal and tumour-induced angiogenesis in vivo and in vitro. This may represent a new front of attack in anti-angiogenic therapies of breast and other cancers.