Study on the real-world emission characteristics of gaseous and particulate pollutants from an inland ship using a portable emission measurement system.

The emissions of pollutants from inland ships endanger the urban environment and human health, deserving quantitative study to make reduction measurements to achieve clean emissions. In this study, the real-world gaseous emissions (CO, THC, SO2, NOx) and particulate emissions including particle mass (PM) and particle number (PN) as well as the particle size distribution and particle compositions from an inland ship were investigated using a portable emission measurement system (PEMS) method. The results showed that the emission concentrations of CO, THC, PM and PN at departure and idling conditions were significantly higher than those at other conditions, while the emission concentrations of NOx and SO2 at cruising condition were the highest. The particle size distribution always presented a bimodal distribution ranged at 40 nm and 200 nm respectively at different conditions and engine loads. The proportion of nucleation mode particles was the highest at departure condition, and a larger engine load resulted in a declined proportion of nucleation mode particles. The anions of the emitted particles mainly included nitrite ion (NO2-), nitrate ion (NO3-), sulfate ion (SO42-), and cations mainly included ammonium ion (NH4+), sodium ion (Na+) and potassium ion (K+). The main components of organic carbon (OC) in soot were OC1 and OC2, accounting for more than 80 %, while the main component of elemental carbon (EC) was EC2, accounting for 83.9 %. The emission factors based on fuel consumption of CO and THC were significantly higher at idling conditions than other conditions, and the emission factor of NOx was higher at cruising conditions, while the emission factors of PM and PN were higher at departure and idling conditions than other conditions.

Experimental Study on Diesel Engine Emission Characteristics Based on Different Exhaust Pipe Coating Schemes.

The thermal insulation performance of exhaust pipes coated with various materials (basalt and glass fiber materials) under different braiding forms (sleeve, winding and felt types) and the effects on the emission characteristics of diesel engines were experimentally studied through engine bench tests. The results indicated that the thermal insulation performance of basalt fiber was higher than that of glass fiber, and more notably advantageous at the early stage of the diesel engine idle cold phase. The average temperature drop during the first 600 s of the basalt felt (BF) pipe was 2.6 °C smaller than that of the glass fiber felt (GF) pipe. Comparing the different braiding forms, the temperature decrease in the felt-type braided material was 2.6 °C and 2.9 °C smaller than that in the sleeve- and winding-type braided materials, respectively. The basalt material was better than the glass fiber material regarding the gaseous pollutant emission reduction performance, especially in the idling cold phase of diesel engines. The NOx conversion rate of the BF pipe was 7.4% higher than that of the GF pipe, and the hydrocarbon (HC) conversion rate was 2.3% higher than that of the GF pipe, while the CO conversion rate during the first 100 s was 24.5% higher than that of the GF pipe. However, the particulate matter emissions were not notably different.

An Efficacy Predictive Method for Diabetic Ulcers Based on Higher-Order Markov Chain-Set Pair Analysis.

BACKGROUND: Clinical comprehensive decision-making of diabetic ulcers includes curative effect evaluation and curative effect prediction. Nevertheless, there are few studies on the prediction of diabetic ulcers. METHODS: Set pair analysis (SPA) was used to assess the curative effect evaluation, and therapeutic effect was evaluated by connection degree (CD). The higher-order Markov chain-SPA curative effect prediction model was established to predict the future curative effect development. The predicted results with higher-order Markov chain-SPA and traditional first-order Markov-SPA model were compared with the actual results of the patients to verify the effectiveness of prediction. RESULTS: The connection degree of index levels I and II of 15 patients with diabetic ulcers after traditional Chinese medicine (TCM) treatment increased with time, while that of index levels IV and V decreased, indicating that the curative effect tends to improve. The higher-order Markov chain-SPA model was used to predict the curative effect. The results showed that the relative errors were fewer than the traditional first-order Markov-SPA model. CONCLUSIONS: The present study suggests that a method of SPA combined with higher-order Markov-SPA is relatively effective and can be applied to the clinical prediction of diabetic ulcers, which has higher accuracy than traditional first-order curative effect prediction model.

Application of a Cloud Model-Set Pair Analysis in Efficacy Assessment for Diabetic Ulcers.

Because treatment of diabetic ulcers includes various uncertainties, efficacy assessments are needed and significant. In previous studies, set pair analysis (SPA) has been applied to the efficacy assessments of traditional Chinese medicine (TCM) that pick out uncertainties related to the development and prognosis of disease. Optimized clinical protocols of SPA improve clinical efficacy. In the article, cloud model (CM) is employed to improve SPA, and a novel efficacy assessment method for a treatment of diabetic ulcers is proposed based on the cloud model-set pair analysis (CM-SPA). It is recommended to replace connection degree (CD) with cloud connection degree (CCD) that the efficacy assessment results are shown as normal clouds. Then, three diabetic ulcers patients treated with TCM made importance assessment by both CM-SPA and AHP based SPA. The comparison of assessment results shows that the CM-SPA is efficacious for the efficacy assessment of a treatment for diabetic ulcers and the results will be more scientific and accurate via CM-SPA.

[Study of syndrome differentiation factor of gouty arthritis with blood stasis syndrome based on connection number].

OBJECTIVE: To find the related syndrome factors of gouty arthritis with blood stasis syndrome by mathematical methods of set pair analysis and connection number so as to guide the diagnosis. METHODS: Seventy gouty arthritis patients diagnosed with blood stasis syndrome were analyzed according to priority by the method of connection number. Syndrome factors of gouty arthritis with blood stasis syndrome were selected according to the numerical values of dialectics connection value (DCV). RESULTS: In the nine observed items, the DCVs of five syndrome factors were above 0.5. These five factors were pain (0.858 0), sublingual varices and positive signs (varices and dark purple color) for palatal mucosa (0.773 1), tophus (0.723 0), varicose veins and telangiectasis (0.700 9), and squamous and dry skin (0.612 3). The DCVs of the other factors were below 0.5. CONCLUSION: The main factor 1 is pain; factor 2 is sublingual varices and positive signs (varices and dark purple color) for palatal mucosa; factor 3 is tophus; factor 4 is varicose veins and telangiectasis; factor 5 is dry skin. The others are secondary factors.

[A connection number-based principal factor analysis forecast method to forecast the encephalitis B epidemics].

OBJECTIVE: To detect the relations between incidence rate of the epidemical encephalitis B and related factors, to provide a simple, valid and practical new method for forecasting encephalitis B eipdemics. METHODS: Connection number between the incidence rate of encephalitis B and the historical forecast factors was computed, before ranking the first, second and the third principal factor, to remove the factor with the smallest value in the light of the connection number before comparing the newest value of forecast factors with the same kind of history while the most nearly value becoming the forecasting factor value and to establish a forecasting equation according to the factor value and the consistent degree of the incidence rate of encephalitis B at that time. Finally, to put into the new factor value to get this forecast value under this equation. Assuming that there are n' (n' >or= 2) forecast factors, this time forecast value can then be directly obtained from the average of these estimate values. RESULTS: Using above forecast method to forecast the incidence rate of encephalitis B at certain place and year, the predicting value is very much close to the actual incidence rate. Difference between the predicting value forecasted by the above-mentioned method and the actual incidence rate is only 0.0264/100 000 with an accurate rate of 97.94%. CONCLUSION: This principal factor analysis forecast method based on connection number in forecasting the incidence rate of encephalitis B prevention is acceptable.