A prediction approach for multichannel EEG signals modeling using local wavelet SVM

Accurate modeling of the multichannel electroencephalogram (EEG) signal is an important issue in clinical practice. In this paper, we propose a new local spatiotemporal prediction method based on support vector machines (SVMs). Combining with the local prediction method, the sequential minimal optimization (SMO) training algorithm, and the wavelet kernel function, a local SMO-wavelet SVM (WSVM) prediction model is developed to enhance the efficiency, effectiveness, and universal approximation capability of the prediction model. Both the spatiotemporal modeling from the measured time series and the details of the nonlinear modeling procedures are discussed. Simulations and experimental results with real EEG signals show that the proposed method is suitable for real signal processing and is effective in modeling the local spatiotemporal dynamics. This method greatly increases the computational speed and more effectively captures the local information of the signal. © 2006 IEEE.published_or_final_versio

Smoking cessation and carotid atherosclerosis: The guangzhou biobank cohort studydCVD

Introduction Smoking has been shown to be associated with carotid atherosclerosis in cross-sectional and prospective studies in Western populations. However, few studies have examined the reversal of risk resulting from quitting smoking, and the results are conflicting. Methods 959 men aged 50e85 years were randomly selected from phase III (2006e2007) of the Guangzhou Biobank Cohort Study into this cross-sectional study. Common carotid artery intima-media thickness (CCAIMT) was measured by B-mode ultrasonography, and carotid artery plaques were identified. Major cardiovascular risk factors, including fasting triglyceride, low-density and high-density lipoprotein (LDL and HDL) cholesterol and glucose, and systolic and diastolic blood pressure, were assessed. Results CCA-IMT and the number of carotid plaque increased from never to former to current smokers (both p≤0.001). Among former smokers compared to current smokers, after adjustment for cigarette pack-years and other potential confounders, the adjusted ORs (95% CI) for quitting for 1-9, 10-19 and 20+ years were 0.77 (0.47 to 1.26), 0.45 (0.26 to 0.79) and 0.37 (0.17 to 0.77) for the presence of CCA atherosclerosis, and 0.69 (0.43 to 1.12), 0.47 (0.27 to 0.82) and 0.45 (0.23 to 0.96) for the presence of carotid plaques, respectively. Longer duration of quitting smoking was also significantly associated with decreasing risk of the severity of CCA atherosclerosis and carotid plaques (all p≤0.001). Conclusion Smoking cessation was beneficial in attenuating the risk of carotid atherosclerosis associated with cigarette smoking. The short duration of cessation in earlier studies is a likely explanation for the inconsistent results.published_or_final_versio

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

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

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—MLR (MLR + BPNN) and MLR-BPNN—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

Synthesis, structure, and magnetism in the ferromagnet La_{3}MnAs_{5}: Well-separated spin chains coupled via itinerant electrons

In this work, we systematically report the synthesis, structure, and magnetism of a compound of filled anti-Mn3Si5 type La3MnAs5. It crystallizes in a hexagonal structure with the space group of P63/mcm (193). The structure consists of face-sharing MnAs6 octahedral chains along the c axis, which are well separated by a large distance of 8.9913 Å, demonstrating a strong one-dimensional (1D) structural character. Physical property measurements indicate that La3MnAs5 is a ferromagnetic metal with TC ∼ 112 K. Due to the short-range intrachain spin coupling, the susceptibility deviates from the Curie-Weiss behavior in a wide temperature window and the magnetic entropy corresponding to the ferromagnetic transition is significantly lower than that expected from the fully saturated state. The magnetic critical behavior studies show that La3MnAs5 can be described by the three-dimensional Heisenberg model. The orbital hybridization between the 1D MnAs6 chain and intermediate La atom near the Fermi level reveals that the itinerant electrons play a key role in transmitting spin interaction among the MnAs6 spin chains. Our results indicate that La3MnAs5 is a rare ferromagnetic metal with well-separated spin chains, which provides a good opportunity to study the mechanism of interchain spin coupling via itinerant electrons

Inactivation Kinetics of beta-N-Acetyl-D-glucosaminidase from Green Crab (Scylla serrata) in Dioxane Solution

Natural Science Foundation of China [40576066, 30500102]; Program for Innovative Research Team in Science and Technology in Fujian Province Universitybeta-N-Acetyl-D-glucosaminidase (NAGase, EC.3.2.1.52), which catalyzes the cleavage of N-acetylglucosamine polymers, is a composition of chitinase and cooperates with endochitinase and exo-chitinase to disintegrate chitin into N-acetylglucosamine (NAG). In this investigation, A NAGase from green crab (Scylla serrata) was purified and the effects of dioxane on the enzyme activity for the hydrolysis of p-Nitrophenyl-N-acetyl-beta-D-glucosaminide (pNP-NAG) were studied. The results show that appropriate concentrations of dioxane can lead to reversible inactivation of the enzyme and the inactivation is classified as mixed type. The value of IC(50), the dioxane (inactivator) concentration leading to 50% activity lost, is estimated to be 0.68%. The kinetics of inactivation of NAGase in the appropriate concentrations of dioxane solution has been studied using the kinetic method of the substrate reaction. The rate constants of inactivation have been determined. The results showed that k(+0) is much larger than k'(+0), indicating the free enzyme molecule is more fragile than the enzyme-substrate complex in the dioxane solution. It is suggested that the presence of the substrate offers marked protection of this enzyme against inactivation by dioxane

The specificity and patterns of staining in human cells and tissues of p16INK4a antibodies demonstrate variant antigen binding

The validity of the identification and classification of human cancer using antibodies to detect biomarker proteins depends upon antibody specificity. Antibodies that bind to the tumour-suppressor protein p16INK4a are widely used for cancer diagnosis and research. In this study we examined the specificity of four commercially available anti-p16INK4a antibodies in four immunological applications. The antibodies H-156 and JC8 detected the same 16 kDa protein in western blot and immunoprecipitation tests, whereas the antibody F-12 did not detect any protein in western blot analysis or capture a protein that could be recognised by the H-156 antibody. In immunocytochemistry tests, the antibodies JC8 and H-156 detected a predominately cytoplasmic localised antigen, whose signal was depleted in p16INK4a siRNA experiments. F-12, in contrast, detected a predominately nuclear located antigen and there was no noticeable reduction in this signal after siRNA knockdown. Furthermore in immunohistochemistry tests, F-12 generated a different pattern of staining compared to the JC8 and E6H4 antibodies. These results demonstrate that three out of four commercially available p16INK4a antibodies are specific to, and indicate a mainly cytoplasmic localisation for, the p16INK4a protein. The F-12 antibody, which has been widely used in previous studies, gave different results to the other antibodies and did not demonstrate specificity to human p16INK4a. This work emphasizes the importance of the validation of commercial antibodies, aside to the previously reported use, for the full verification of immunoreaction specificity