Synchrony of clinical and laboratory surveillance for influenza in Hong Kong

Background: Consultation rates of influenza-like illness (ILI) in an outpatient setting have been regarded as a good indicator of influenza virus activity in the community. As ILI-like symptoms may be caused by etiologies other than influenza, and influenza virus activity in the tropics and subtropics is less predictable than in temperate regions, the correlation between of ILI and influenza virus activity in tropical and subtropical regions is less well defined. Methodology and Principal Findings: In this study, we used wavelet analysis to investigate the relationship between seasonality of influenza virus activity and consultation rates of ILI reported separately by General Out-patient Clinics (GOPC) and General Practitioners (GP). During the periods 1998-2000 and 2002-2003, influenza virus activity exhibited both annual and semiannual cycles, with one peak in the winter and another in late spring or early summer. But during 2001 and 2004-2006, only annual cycles could be clearly identified. ILI consultation rates in both GOPC and GP settings share a similar non-stationary seasonal pattern. We found high coherence between ILI in GOPC and influenza virus activity for the annual cycle but this was only significant (P<0.05) during the periods 1998-1999 and 2002-2006. For the semiannual cycle high coherence (p<0.05) was also found significant during the period 1998-1999 and year 2003 when two peaks of influenza were evident. Similarly, ILI in GP setting is also associated with influenza virus activity for both the annual and semiannual cycles. On average, oscillation of ILI in GP and of ILI in GOPC preceded influenza virus isolation by approximately four and two weeks, respectively. Conclusions: Our findings suggest that consultation rates of ILI precede the oscillations of laboratory surveillance by at least two weeks and can be used as a predictor for influenza epidemics in Hong Kong. The validity of our model for other tropical regions needs to be explored. © 2008 Yang et al.published_or_final_versio

Inference of Allelopathy about Spartina Alterniflora to Scirpus Mariqueter by Effects of Activated Carbon on Soil

AbstractSpartina alterniflora Loisel is an invasive species in Jiuduansha Islands and threatens the survival of native species Scirpus mariqueter. In this study, activated carbon (AC) was applied to study the allelochemicals remained in the soil. Seed germination and seedling growth bioassays were used to test the allelopathic effect, and GC-MS was used to identify the allelochemicals. Our results showed: due to the invasion of S. alterniflora, germination of S. mariqueter seeds and the growth of seedlings were significantly inhibited. When AC was added into S. mariqueter soil, the germination had not been affected while the seedling growth was promoted significantly. When AC was added into the soil of S. alterniflora, both the germination and the seedling growth had an obvious improvement. All indicated that S. alterniflora soil contained allelochemicals which would be absorbed by AC. The identified allelochemicals were hexadecanoic acid, octadecanoic acid, dibutyl phthalate, (adipic acid, isohexyl methyl ester) and (adipic acid, di (oct-4-yl ester))

Effects of Landscape Design on Urban Microclimate and Thermal Comfort in Tropical Climate

A climate-responsive landscape design can create a more livable urban microclimate with adequate human comfortability. This paper aims to quantitatively investigate the effects of landscape design elements of pavement materials, greenery, and water bodies on urban microclimate and thermal comfort in a high-rise residential area in the tropic climate of Singapore. A comprehensive field measurement is undertaken to obtain real data on microclimate parameters for calibration of the microclimate-modeling software ENVI-met 4.0. With the calibrated ENVI-met, seven urban landscape scenarios are simulated and their effects on thermal comfort as measured by physiologically equivalent temperature (PET) are evaluated. It is found that the maximum improvement of PET reduction with suggested landscape designs is about 12°C, and high-albedo pavement materials and water bodies are not effective in reducing heat stress in hot and humid climate conditions. The combination of shade trees over grass is the most effective landscape strategy for cooling the microclimate. The findings from the paper can equip urban designers with knowledge and techniques to mitigate urban heat stress

Tai Chi for Chronic Pain Conditions: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Several studies reported that Tai Chi showed potential effects for chronic pain, but its role remains controversial. This review assessed the evidence regarding the effects of Tai Chi for chronic pain conditions. 18 randomized controlled trials were included in our review. The aggregated results have indicated that Tai Chi showed positive evidence on immediate relief of chronic pain from osteoarthritis (standardized mean difference [SMD],-0.54; 95% confidence intervals [CI],-0.77 to-0.30; P < 0.05). The valid duration of Tai Chi practice for osteoarthritis may be more than 5 weeks. And there were some beneficial evidences regarding the effects of Tai Chi on immediate relief of chronic pain from low back pain (SMD,-0.81; 95% CI,-1.11 to-0.52; P < 0.05) and osteoporosis (SMD,-0.83; 95% CI,-1.37 to-0.28; P = 0.003). Therefore, clinicians may consider Tai Chi as a viable complementary and alternative medicine for chronic pain conditions

Design optimization considering variable thermal mass, insulation, absorptance of solar radiation, and glazing ratio using a prediction model and genetic algorithm

This paper presents the optimization of building envelope design to minimize thermal load and improve thermal comfort for a two-star green building in Wuhan, China. The thermal load of the building before optimization is 36% lower than a typical energy-efficient building of the same size. A total of 19 continuous design variables, including different concrete thicknesses, insulation thicknesses, absorbance of solar radiation for each exterior wall/roof and different window-to-wall ratios for each façade, are considered for optimization. The thermal load and annual discomfort degree hours are selected as the objective functions for optimization. Two prediction models, multi-linear regression (MLR) model and an artificial neural network (ANN) model, are developed to predict the building thermal performance and adopted as fitness functions for a multi-objective genetic algorithm (GA) to find the optimal design solutions. As compared to the original design, the optimal design generated by the MLRGA approach helps to reduce the thermal load and discomfort level by 18.2% and 22.4%, while the reductions are 17.0% and 22.2% respectively, using the ANNGA approach. Finally, four objective functions using cooling load, heating load, summer discomfort degree hours, and winter discomfort degree hours for optimization are conducted, but the results are no better than the two-objective-function optimization approach

A Review of Recent Advances in Research on PM2.5 in China

PM2.5 pollution has become a severe problem in China due to rapid industrialization and high energy consumption. It can cause increases in the incidence of various respiratory diseases and resident mortality rates, as well as increase in the energy consumption in heating, ventilation, and air conditioning (HVAC) systems due to the need for air purification. This paper reviews and studies the sources of indoor and outdoor PM2.5, the impact of PM2.5 pollution on atmospheric visibility, occupational health, and occupants’ behaviors. This paper also presents current pollution status in China, the relationship between indoor and outdoor PM2.5, and control of indoor PM2.5, and finally presents analysis and suggestions for future research

Preparation and analysis of a new bioorganic metallic material

Biofouling on metal surfaces is one of the main reasons for increased ship drag. Many methods have already been used to reduce or remove it with moderate success. In this study, a synthetic peptide has been utilized to react with 304 stainless steel aiming to generate a bioorganic stainless steel using a facile technique. After the reaction, white matter was found on the surface of the treated stainless steel via SEM, whilst the nontreated stainless steel had none. Elemental analysis confirmed that excessive N existed on the surface of the treated samples using an integrated SEM-EDS instrument, implying the presence of peptides binding on the surface of the bioorganic stainless steel. The FTIR spectra showed amide A and II peaks on the surface of the bioorganic stainless steel suggesting that either the peptides grafted onto the steel surface or the polypeptide composition accumulated on the steel samples. XPS analysis of the treated steel demonstrated that there was nitrogen bonding on the surface and it was a chemical bond via a previously unreported chemical interaction. The treated steel has a markedly increased contact angle (water contact angle of 65.7 ± 4.7° for nontreated steel in comparison to treated, 96.4 ± 2.1°), which supported the observation of the wettability change of the surface, i.e. the decrease of the surface energy value after peptide treatment. The changes of the surface parameters (such as, Sa, Sq, Ssk and Sku) of the treated steel by surface analysis were observed

Development of Building Thermal Load and Discomfort Degree Hour Prediction Models Using Data Mining Approaches

Thermal load and indoor comfort level are two important building performance indicators, rapid predictions of which can help significantly reduce the computation time during design optimization. In this paper, a three-step approach is used to develop and evaluate prediction models. Firstly, the Latin Hypercube Sampling Method (LHSM) is used to generate a representative 19-dimensional design database and DesignBuilder is then used to obtain the thermal load and discomfort degree hours through simulation. Secondly, samples from the database are used to develop and validate seven prediction models, using data mining approaches including multilinear regression (MLR), chi-square automatic interaction detector (CHAID), exhaustive CHAID (ECHAID), back-propagation neural network (BPNN), radial basis function network (RBFN), classification and regression trees (CART), and support vector machines (SVM). It is found that the MLR and BPNN models outperform the others in the prediction of thermal load with average absolute error of less than 1.19%, and the BPNN model is the best at predicting discomfort degree hour with 0.62% average absolute error. Finally, two hybrid models&mdash;MLR (MLR + BPNN) and MLR-BPNN&mdash;are developed. The MLR-BPNN models are found to be the best prediction models, with average absolute error of 0.82% in thermal load and 0.59% in discomfort degree hour

Is exercise protective against influenza-associated mortality?

Background: Little is known about the effect of physical exercise on influenza-associated mortality. Methods and Findings: We collected information about exercise habits and other lifestyle, and socioeconomic and demographic status, the underlying cause of death of 24,656 adults (21% aged 30-64, 79% aged 65 or above who died in 1998 in Hong Kong, and the weekly proportion of specimens positive for influenza A (H3N1 and H1N1) and B isolation during the same period. We assessed the excess risks (ER) of influenza-associated mortality due to all-natural causes, cardiovascular diseases, or respiratory disease among different levels of exercise: never/seldom (less than once per month), low/moderate (once per month to three times per week), and frequent (four times or more per week) by Poisson regression. We also assessed the differences in ER between exercise groups by case-only logistic regression. For all the mortality outcomes under study in relation to each 10% increase in weekly proportion of specimens positive for influenza A+B, never/seldom exercise (as reference) was associated with 5.8% to 8.5% excess risks (ER) of mortality (P<0.0001), while low/moderate exercise was associated with ER which were 4.2% to 6.4% lower than those of the reference (P<0.001 for all-natural causes; P=0.001 for cardiovascular; and P=0.07 for respiratory mortality). Frequent exercise was not different from the reference (change in ER -0.8% to 1.7%, P=0.30 to 0.73). Conclusion: When compared with never or seldom exercise, exercising at low to moderate frequency is beneficial with lower influenza-associated mortality. © 2008 Wong et al.published_or_final_versio