Research on the removal characteristics of surface error with different spatial frequency based on shear thickening polishing method.

X-ray mirrors, which are essential for constructing synchrotron radiation light sources, are highly required for full-range spatial wavelength errors. This paper investigated power-law non-Newtonian fluids and pointed out that both three-body removal and shear removal existed in the shear thickening polishing process. Subsequently, this paper calculates the shear force of the power-law non-Newtonian fluid polishing fluid in polishing the surface with different frequency errors. It establishes an MRR model of shear thickening polishing in the frequency domain by combining it with the Archard equation. Then, this model is also applied to optimize the polishing fluid formulation and processing parameters. Finally, the removal effect of the optimized polishing fluid on the mid-frequency ripple error is experimentally verified. On Ф50 mm monocrystalline silicon, the removal of mid-frequency ripple error with a spatial wavelength of 1 mm was achieved by shear thickening polishing technique while converging the surface roughness to 0.14 nm. Finally, the experimental results were applied to monocrystalline silicon with a length of 500 mm. This work provides a new research idea for the existing shear thickening polishing process. It provides theoretical and technical support for removing the mid- and high-frequency errors in high-precision X-ray mirrors.

Inkjet printed uniform quantum dots as color conversion layers for full-color OLED displays.

Quantum dots (QDs) have shown great potential for next generation displays owing to their fascinating optoelectronic characteristics. In this work, we present a novel full-color display based on blue organic light emitting diodes (BOLEDs) and patterned red and green QD color conversion layers (CCLs). To enable efficient blue-to-green or blue-to-red photoconversion, micrometer-thick QD films with a uniform surface morphology are obtained by utilizing UV-induced polymerization. The uniform QD layers are directly inkjet printed on red and green color filters to further eliminate the residual blue emissions. Based on this QD-BOLED architecture, a 6.6-inch full-color display with 95% Broadcasting Service Television 2020 (BT.2020) color gamut and wide viewing-angles is successfully demonstrated. The inkjet printing method introduced in this work provides a cost-effective way to extend the applications of QDs for full-color displays.

Vacuum-Drying Processed Micrometer-Thick Stable CsPbBr3 Perovskite Films with Efficient Blue-To-Green Photoconversion.

Metal halide perovskite materials have attracted great attention owing to their fascinating optoelectronic characteristics and low cost fabrication via facile solution processing. One of the potential applications of these materials is to employ them as color-conversion layers (CCLs) for visible blue light to achieve full-color displays. However, obtaining thick perovskite films to realize complete color conversion is a key challenge. Here, the fabrication of micrometer-level thick CsPbBr3 perovskite films is presented through a facile vacuum drying approach. An efficient green photoconversion is realized in a 3.8 µm thick film from blue light @ 463 nm. For a back luminance of 1000 cd m-2 , the brightness of the resulting green emission can reach as high as 200 cd m-2 . Furthermore, only ≈2% of decay in brightness is observed when the films are tested after 18 days of exposure to ambient environment. In addition, a potential design is also proposed for full-color displays with perovskite materials incorporated as CCLs.

Alloying Strategy in Cu-In-Ga-Se Quantum Dots for High Efficiency Quantum Dot Sensitized Solar Cells.

I-III-VI2 group "green" quantum dots (QDs) are attracting increasing attention in photoelectronic conversion applications. Herein, on the basis of the "simultaneous nucleation and growth" approach, Cu-In-Ga-Se (CIGSe) QDs with light harvesting range of about 1000 nm were synthesized and used as sensitizer to construct quantum dot sensitized solar cells (QDSCs). Inductively coupled plasma atomic emission spectrometry (ICP-AES), wild-angle X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) analyses demonstrate that the Ga element was alloyed in the Cu-In-Se (CISe) host. Ultraviolet photoelectron spectroscopy (UPS) and femtosecond (fs) resolution transient absorption (TA) measurement results indicate that the alloying strategy could optimize the electronic structure in the obtained CIGSe QD material, thus matching well with TiO2 substrate and favoring the photogenerated electron extraction. Open circuit voltage decay (OCVD) and impedance spectroscopy (IS) tests indicate that the intrinsic recombination in CIGSe QDSCs was well suppressed relative to that in CISe QDSCs. As a result, CIGSe based QDSCs with use of titanium mesh supported mesoporous carbon counter electrode exhibited a champion efficiency of 11.49% (Jsc = 25.01 mA/cm2, Voc = 0.740 V, FF = 0.621) under the irradiation of full one sun in comparison with 9.46% for CISe QDSCs.

Improving Loading Amount and Performance of Quantum Dot-Sensitized Solar Cells through Metal Salt Solutions Treatment on Photoanode.

Increasing QD loading amount on photoanode and suppressing charge recombination are prerequisite for high-efficiency quantum dot-sensitized solar cells (QDSCs). Herein, a facile technique for enhancing the loading amount of QDs on photoanode and therefore improving the photovoltaic performance of the resultant cell devices is developed by pipetting metal salt aqueous solutions on TiO2 film electrode and then evaporating at elevated temperature. The effect of different metal salt solutions was investigated, and experimental results indicated that the isoelectric point (IEP) of metal ions influenced the loading amount of QDs and consequently the photovoltaic performance of the resultant cell devices. The influence of anions was also investigated, and the results indicated that anions of strong acid made no difference, while acetate anion hampered the performance of solar cells. Infrared spectroscopy confirmed the formation of oxyhydroxides, whose behavior was responsible for QD loading amount and thus solar cell performance. Suppressed charge recombination based on Mg2+ treatment under optimal conditions was confirmed by impedance spectroscopy as well as transient photovoltage decay measurement. Combined with high-QD loading amount and retarded charge recombination, the champion cell based on Mg2+ treatment exhibited an efficiency of 9.73% (Jsc = 27.28 mA/cm2, Voc = 0.609 V, FF = 0.585) under AM 1.5 G full 1 sun irradiation. The obtained efficiency was one of the best performances for liquid-junction QDSCs, which exhibited a 10% improvement over the untreated cells with the highest efficiency of 8.85%.

[Spatial distribution and risk factors of tuberculosis in Songjiang district, Shanghai during 2006 and 2009].

OBJECTIVE: To identify spatial distribution and risk factors among tuberculosis (TB) cases in Songjiang district, Shanghai, 2006 - 2009. METHODS: All active TB cases and all bacteriologically confirmed TB cases diagnosed during the period from 2006 to 2009 were recruited into the study. Spatial scan statistics were used to identify spatial clusters. Using logistic regression, we compared the demographic and clinical characteristics of TB cases in spatial clusters versus TB cases not in spatial clusters. RESULTS: A total of 1815 active TB cases and 730 bacteriologically confirmed TB cases were recruited during 2006 - 2009. Chedun township and Xinqiao township was detected to be a spatial cluste (RR = 1.38, LLR = 16.78, P < 0.01), which was the location of the municipal industrial zone. No spatial cluster was found during 2006 - 2007, while during 2008 - 2009 Chedun township was detected to be a spatial cluster (RR = 1.70, LLR = 15.06, P < 0.01). Among resident population, the spatial cluster of TB cases was located in the southwestern part of Songjiang district, which included five townships Xinbang, Shihudang, Xiaokunshan, Maogang and Yongfeng (RR = 1.49, LLR = 10.52, P < 0.01); while among migrant population, the spatial cluster of TB cases was located in Chedun township (RR = 1.55, LLR = 15.64, P < 0.01). There were higher proportions of resident TB cases who were farmers (AOR = 4.9, 95%CI: 1.9 - 12.3) or had other occupations (AOR = 2.6, 95%CI: 1.1 - 5.9) in the spatial cluster. There were higher proportions of migrant TB cases who lived here for less than 5 years (< 1 year: AOR = 5.9, 95%CI: 1.8 - 19.5; 1 - 5 years: AOR = 3.2, 95%CI: 1.0 - 9.9) or worked at other occupations (AOR = 2.8, 95%CI: 1.5 - 5.1) and lower proportions of migrant TB cases who came from Eastern region (AOR = 0.3, 95%CI: 0.1 - 0.8) or Middle region (AOR = 0.5, 95%CI: 0.3 - 0.9) in the spatial cluster. CONCLUSION: In Songjiang district there was a spatial cluster in TB cases, which was Chedun township. Local residents with TB who were farmers or had other occupations were more likely to be in the spatial cluster. Migrants with TB who lived here for less than 5 years or came from Western region were more likely to be in the spatial cluster.

Spatial analysis of hepatocellular carcinoma and socioeconomic status in China from a population-based cancer registry.

BACKGROUND: Little is known about geographic variations in liver cancer at high incident regions. We aimed to identify spatial variation of hepatocellular carcinoma (HCC) at a high-risk area in China and determine its association with socioeconomic status (SES). METHODS: Based on 2299 liver cancer cases diagnosed in Haimen from 2003 to 2006, we calculated age-sex standardized incidence ratios (SIRs) and used two spatial scan statistics to determine the geographic variations in HCC. Bayesian hierarchical model was used to explore the association between HCC incidence and SES. RESULTS: Age and sex SIRs for HCC varied from 0.54 to 1.97 for 24 townships. The eastern region of Haimen was identified to have a significantly increased risk of HCC. Fitting of a Bayesian hierarchical model linking per-capita fiscal revenue with SIRs of HCC indicated that the area with a lower revenue had a significantly higher incidence of HCC [beta(log(revenue))=-0.179, posterior 95% Bayesian credible interval (CI)=(-0.326, -0.04)]. CONCLUSIONS: This study demonstrated substantial geographic variation in the incidence of HCC within a high-risk region, which was associated with SES. HCC control and intervention should focus on disadvantaged areas to reduce the HCC disparities.

Nonparametric spatial analysis to detect high-risk regions for schistosomiasis in Guichi, China.

Schistosomiasis control in China is facing a new challenge due to the rebound of epidemics in many areas and the unsustainable effects of the chemotherapy-based control strategy. Identifying high-risk regions for schistosomiasis is an important first step for an effective and sustainable strategy. Direct surveillance of snail habitats to detect high-risk regions is costly and no longer a desirable approach, while indirect monitoring of acute schistosomiasis may be a satisfactory alternative. To identify high-risk regions for schistosomiasis, we jointly used multiplicative and additive models with the kernel smoothing technique as the main approach to estimate the relative risk (RR) and excess risk (ER) surfaces by analyzing surveillance data for acute schistosomiasis. The feasibility of detecting high-risk regions for schistosomiasis through nonparametric spatial analysis was explored and confirmed in this study, and two significant high-risk regions were identified. The results provide useful hints for improving the national surveillance network for acute schistosomiasis and possible approaches to utilizing surveillance data more efficiently. In addition, the commonly used epidemiological indices, RR and ER, are examined and emphasized from the spatial point of view, which will be helpful for exploring many other epidemiological indices.

[Study on the quantified indices to describe the distributional status of diseases in the spatial point pattern analysis].

OBJECTIVE: To study the quantified indices for describing the distributional status of diseases in the spatial point pattern analysis, and provide the a statistic in disease prevention and control. METHODS: G function, F function, J function and K function were summarized based on the inter-case distances from the view of spatial point pattern analysis. Through the introduction of the basic principles, these were used to analyze the data of acute schistosomiasis in the Guichi District, Chizhou City, Anhui province, with the study distances being from 0 to 3000 meters with 50-meter intervals. The findings were also validated by means of spatial moving scan window performed in SaTScan software. RESULTS: A total of 83 cases of acute schistosomiasis identified in Guichi District, and the point map showed that these cases were mainly distributed around the Yangtze and Qiupu rivers. The computational methods and characteristics of the four quantified indices were obtained. These acute schistosomiasis cases were also explored by using these indices, and the results showed that C and K functions were above 95% confidence interval. While, F and J functions were below 95% confidence interval. Ml these four indices showed that spatial clustering existed in the acute cases, which was consistent with the results of spatial moving scan window method. The latter method also found a most likely cluster, the coordinate of the circle center is (30.65 N, 117.44 E), radius is 2.69 km, and relative risk is 12.78 (DIR = 32. 80, P = 0. 0001). CONCLUSION: The quantified indices to describe the distributional status of diseases have not only solved the obstacle that spatial point pattern map which could only be analyzed qualitatively, but also supplied a theoretical foundation to deepen spatial clustering analysis. OBJECTIVE: To study the quantified indices for describing the distributional status of

Identifying high-risk regions for schistosomiasis in Guichi, China: a spatial analysis.

Schistosomiasis epidemic is reemerging in some areas of China. The extensive snail habitat is a major challenge for a sustainable schistosomiasis control. Direct surveillance on snails for the disease control is no longer a desirable disease control approach due to current low density of infected snails and reduced funding. In this study the benefit of indirect monitoring of acute schistosomiasis cases, using spatial methods including disease mapping and spatial clustering analysis was explored in Guichi, China. Significant global clustering existed for acute cases and two statistically significant spatial clusters were detected, and subsequently validated by field surveys. Our study indicates that the application of geographic information system (GIS) and spatial methods are useful in the epidemiologic surveillance and risk assessment for acute schistosomiasis, providing an alternative approach with minimal funds required.

[Spatial distribution pattern of Oncomelania hupensis population in marshland and lake area].

OBJECTIVE: To explore the spatial pattern of the distribution of Oncomelania hupensis population in marshland and lake region. METHODS: Four bottomlands were selected randomly for the investigation along the Qiupu River in Guichi District, Anhui Province. The quadrats were placed randomly for snail survey, and the mean crowding, mean density, aggregation indices (diffusion coefficient (C), morisita index (Idelta), index of patchiness (m*/m) ), Taylor's power law and Iwao's m*-m regression index were analyzed. RESULTS: For 4 bottomlands in different time, the diffusion coefficients, Morisita indices, and m*/m indices were all more than one. There was a close linear relationship between the logarithm of the snail density and its variance (P < 0.01), and the correlation coefficient was 0.972. In Taylor's power law, the lg a was 0.602 and b was 1.427. There was a close linear relationship between the mean crowding (m*) and the snail density (m) (P < 0.01), and the correlation coefficient, alpha and beta was 0.984, 2.367 and 1.617 respectively. CONCLUSION: The spatial pattern of Oncomelania hupensis population shows an aggregation distribution in marshland and lake region, and the basic components of snail distribution are in colonies.

A model for the prediction of Oncomelania hupensis in the lake and marshland regions, China.

A model has been developed for predicting the density of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum. The model takes into account different environmental factors, including elevation, air and soil temperature, type of vegetation, mean height of preponderant vegetation and soil humidity. Deviance and Akaike information criteria were used to determine the best model fits. Model diagnostics and internal and external validations of model efficiency were also performed. From the final prediction model, two important results emerge. First, air temperature should be used with care to study the distribution of O. hupensis and to predict its potential survival because the impact is indirect, and it is weaker and more unstable than soil temperature. Second, the more important environmental factor for O. hupensis prediction at the microscale is soil humidity, but the more important macroscale environmental factor is soil temperature. This finding might help in selecting different environmental features for studying O. hupensis at different spatial scales. Our model is promising for predicting the density of O. hupensis, and hence can provide more objective information about snail dispersal, which might eventually replace the tedious and imprecise field work for annual surveillance of O. hupensis.

Field comparison of immunodiagnostic and parasitological techniques for the detection of Schistosomiasis japonica in the People's Republic of China.

A total of 1,811 individuals from two villages located in the areas of China endemic for Schistosoma japonicum were analyzed by the Kato-Katz parasitologic examination, indirect hemagglutination assay (IHA), and enzyme-linked immunosorbent assay (ELISA). Statistical analysis of the results showed the kappa indices ranged from 0.106 to 0.234 between IHA and the stool examination and ranged from 0.037 to 0.134 between ELISA and the fecal examination. The sensitivity value of the IHA was 83.7% in Village A and 92.3% in Village B; the specificity value of the IHA was 55.8% in Village A and 67.3% in Village B. The sensitivity value of the ELISA was 88.4% in Village A and 96.2% in Village B; the specificity value of the ELISA was 38.4% in both Village A and Village B. A search for a good diagnostic test that can be applied in field situations in China should be given high priority.

[Linear models for predicting of Oncomelania hupensis in the lake and marsh regions].

OBJECTIVE: To study the prediction model of O. hupensis in the lake and marshland regions in order to provide methodological basis for quantitative study of O. hupensis. METHODS: The research sites were randomly selected from the bottomlands along Qiupu River in the Guichi District, Anhui Province. A random and stratified sampling method was administrated according to the type of vegetation; the frame size of snail survey was 0.11 m2. Snail data was collected by crosscheck-random sampling inspection survey. Elevation, soil temperature and air temperature, height of vegetation, soil humidity and types of vegetation were measured through GPS machine, T&D Recorder for Windows, tape measure and attemperator. All the data were doubly inputted into the computer and checked. The final dataset for developing the prediction model was set up after necessary data preprocessing, such as, recoding the variable of elevation. The generalized linear models were used to develop the prediction model, and the statistics of deviance and AIC were used to determine the best model structure. Model diagnostics and model evaluation of efficiency were performed with the determined best model structure. RESULTS: The sample size was 162, and there were 6 explanatory variable including 2 categorical variables and 4 quantitative variables. A complicated relationship was observed among all the variables. Snail was positively associated with height of vegetation (r = 0.36), while negatively associated with soil humidity (r = - 0.22), and the air temperature had a close positive relations with soil temperature (r = 0.59), and the soil temperature was negatively associated with height of vegetation (r = - 0.36), the soil humidity had negative relations with the soil and air temperature (r = -0.34 and -0.12). The best structure fitting for the liner model selected in gamma distribution was the error distribution, reciprocal as the conjunction function in mathematics, and the mean square as the variance function. The results showed that the elevation, soil humidity, soil temperature, types and the height of vegetation were statistically significant to predict the O. hupensis, while t-values were -3.202, 3.124, -1.989, 2.668 and -2.371, respectively, and P-values were 0.00166, 0.00214, 0.04849, 0.00846 and 0.01897 respectively. CONCLUSION: The generalized linear models can be used to develop the predictive model, which could broaden the area of quantitative study for O. hupensis.