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Air pollution and its negative effects on health of people have been a global concern. Many studies had found a strong association between air pollutants and risk of death, but few had focused on the effects of six pollutants and rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO2, O3, PM2.5, PM10, and SO2) on non-accidental and respiratory deaths in rural areas of Anhui Province by adjusting for confounding factors, and to further clarify which populations were susceptible to death associated with air pollution. In the first phase of the analysis, the generalized additive models were combined with the distributed lag non-linear models to evaluate the individual effects of air pollution on death in each area. In the second stage, random-effects models were used to aggregate the associations between air pollutants and mortality risk in nine areas. Overall, six pollutants had the strongest effects on the risk of death on the lag 07 days. The associations between PM2.5 and NO2 and daily non-accidental deaths were strongest, with maximum RR (lag 07): 1.63 (1.37-1.88) and 1.67 (1.37-1.96). The maximum pooled effects of association between six air pollutants and RD were PM2.5, with RR (lag 07): 1.89 (1.45-2.34). PM2.5 and PM10 had significant differences between the elderly and the non-elderly with respectively, RRR: 1.22 (1.04-1.41) and 1.26 (1.11-1.42). In general, we found that six air pollutants were the important risk factors for deaths (deaths from respiratory disease and non-accidental) in rural areas of Anhui Province. PM10 and PM2.5 had a considerable impact on the elderly.

It is unclear whether weight change after middle adulthood influences the risk of thyroid cancer. The aim of this study was to investigate associations between the risk of papillary thyroid cancer (PTC) and body mass index (BMI) and weight change after middle adulthood (age 35).A matched case-control study based on three hospitals included 516 pairs of cases newly diagnosed with PTC and controls. Current height and weight after defecation in the morning were measured by trained nurses. During measurement, all subjects were requested to wear lightweight clothing and no shoes. Weight at age 35 was self-reported. BMI and weight change were modeled as continuous and categorical variables. Conditional and unconditional logistic regression models were used to estimate the odds ratio (OR) and 95% confidence interval (95%CI) for the association between BMI and weight change after middle adulthood and PTC.After adjustment for covariates, measured BMI at the time of current diagnosis was positively associated with PTC (OR 1.16, 95%CI 1.10-1.21). According to WHO BMI guidelines for Asia-Pacific populations, the OR (95%CI) for PTC risk in obesity was 2.99 (1.92-4.67) compared to normal weight (p-trend0.001). Moreover, PTC was positively associated with BMI at age 35; the OR (95%CI) for PTC risk per unit increase in BMI was 1.06 (1.02-1.11). Compared to stable weight (changed0.5 kg/year), weight gain ≥1.0 kg/year after middle adulthood was positively associated with PTC (OR 2.57, 95%CI 1.39-4.76, p-trend0.001). Compared to maintaining non-overweight status, the PTC risk was significantly increased in those individuals who gained weight and became overweight after middle adulthood (OR 3.82, 95%CI 2.50-5.85).This study showed that high BMI and obesity were positively associated with increased risk of PTC, and weight gain after middle adulthood also could elevate the PTC risk.

Background: Thyroid cancer (TC) has inflicted huge threats to the health of mankind. Chlorophenols (CPs) were persistent organic pollutant and can lead to adverse effects in human health, especially in thyroid. However, epidemiological studies have revealed a rare and inconsistent relationship between internal exposure to CPs and TC risk. This study was designed to examine the association between urinary CPs and risk of TC in Chinese population.Methods: From June 2017 to September 2019, a total of 297 histologically confirmed TC cases were recruited. Age and gender matched controls were enrolled at the same time. Gas chromatography-mass spectrometry (GC-MS) was used to determine the levels of three CPs in urine. Conditional logistic regression models were adopted to assess the potential association. Restricted cubic spline function was used to explore the non-liner association.Results: After adjusting for confounding factors, multivariate analysis showed that, compared with the first quartile, the fourth quartile concentrations of 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol (2,4,6-TCP) and pentachlorophenol(PCP) were associated with TC risk [odds ratio (OR)2,4-DCP =2.28, 95%confidence interval (CI): 1.24-4.18; OR2,4,6-TCP =3.09, 95% CI: 1.66-5.77; ORPCP =3.30, 95% CI: 1.71-6.36, respectively]. When CPs were included in the multivariate model and restricted cubic spline function as continuous variables, presenting significant dose-response relationships. Meanwhile, whether in the TC group with tumor diameter > 1 cm or metastatic TC, the changes of 2,4,6 TCP and PCP concentrations were positively correlated with the risk of TC. Conclusions: Our study suggests that higher concentrations of urinary CPs are associated with increased TC risks. Moreover, 2,4,6-TCP and PCP have certain effects on the invasiveness of thyroid cancer. Targeted public health policies should be formulated to reduce the CPs pollution. These findings need further in-depth studies to confirm and relevant mechanism also needed to be clarified.

The mean wind speed, wind speed distribution, wind shear exponent and wind power density would be affected by terrain, atmospheric stability and equipments, are important parameters in the process of wind resource assessment. However, Conventional methods have always ignored the effects of atmospheric stability, which might make results deviate from the actual situation. The main purpose of this work is to present effects of atmospheric stability on wind resource parameters. Taking 4 years’ measured data as case study, six parameters in wind resource assessing are calculated under different atmospheric stabilities; influential rules of above assessing parameters under varying atmospheric stability are analyzed respectively in order to obtain a systemic relationship between atmospheric stability and wind resource characteristic parameters which is tested by 5th year’s data. Based on these studies, a hub height wind speed extrapolation model is proposed. This model could use different wind shear exponent under various atmospheric stabilities during wind speed extrapolating, rather than an average wind shear for the whole wind farm. In such way, much accurate extrapolating hub wind speed in wind resource assessing is employed, and errors in wind resource assessment might decline. Results validate the simplicity, accuracy and practicality of the proposed method.

The load-carrying capacity and the stability of wind power generation are different from those of conventional generation. The current evaluation method almost considers the capacity credit of each region as a fixed value, which underestimates the contribution of wind power generation to the power system adequacy. To solve this problem, the wind power continuous output model is proposed in this paper based on the nonparametric joint probability density distribution of prediction error. This model can well describe the wind power output but is complicated. Improved wind power two-state model is developed. Under the condition that expected energy not supplied (EENS) is unchangeable, various wind power operating capacity credit, defined by equivalent firm capacity (EFC), equivalent conventional generation capacity (ECGC) and equivalent load-carrying capability (ELCC), is evaluated by both models with measurements and predictions. It can be observed that the results calculated by the proposed models are similar, and they are more reasonable and effective than the existing models.

Pilots' fatigue status could influence aviation safety. The recognition of fatigue status of pilots is of utmost significance. We proposed a new deep learning model via analyzing electroencephalogram signals to reduce the complexity of feature extraction and improve the accuracy of recognition of fatigue status of pilots. We firstly applied wavelet packet transform to decompose electroencephalogram signals of pilots to extract the δ wave (1∼3 Hz), θ wave (4∼7 Hz), α wave (8∼13 Hz) and β wave (14∼30 Hz), and the combined representation of them were de-nosing EEG signals. Then we used proposed deep sparse auto-encoding network to reduce the complexity of de-nosing EEG signals and gained learning features. Lastly, we applied Softmax classifier on learning features and the experimental results showed that the proposed deep learning model had a nice recognition, and the accuracy of recognition was up to 91.67%, which meant that the proposed method performed excellently compared with the state-of-art methods.

In order to characterize the temperature regulating ability of fabrics containing phase change material (PCM), the test has been designed. To assess temperature regulating ability, temperature regulating factor (TRF) is determined. TRF is defined as a quotient of the amplitude of the temperature variation of the hot plate and the amplitude of the heat flux variation divided by the steady state heat resistance of the fabric. The test instrument presented here is intended to be used for testing steady state and transient state characteristics of the apparel fabrics containing the PCMs. This test instrument can be used in quality control during the manufacture of fabrics containing PCMs. TRF can be used in clothing industry to establish the criteria for comfort parameters of textiles.

On the basis of the UMHexagonS algorithm used in the Joint Model(JM) for H.264,a new fast algorithm on integer pixel motion estimation was proposed to improve the video encoding characteristics.A new order of checking predicted Motion Vector(MV) was proposed in the predicting starting search point to promote the accuracy of starting search point.Then,a self-adaptive global search method was proposed for the global search,by which the unsymmetrical-cross search and uneven multi-hexagon-grid search could be skipped based on the relationship between two predicted MVs with highest accuracy,and the feasibility and accuracy of this judging method was verified through tests on a number of different sequences.Meanwhile,an improved 5×5 search method was presented according to the distribution of best MV relative to the starting search point and a new early termination technique for sub-macroblock was added to further reduce the cost of motion estimation without additional computation.According to the experiment results,the proposed algorithm reduces the total number of search points by 83.80% and the Peak Signal to Noise Ratio(PSNR) about 0.021 dB on average and increases an average increment of 0.46% on equivalent bitrates as compared with that of original UMHexagonS algorithm.With a negligible performance degradation,the proposed algorithm reduces the computation of motion estimation effectively and offers a well-distributed effect on sequences with different motion intensities.

For the unreliable data storage problem caused by bad blocks and single event upsets for the NAND flash memory in a space camera,this paper explores a bad block management strategy and an error correction algorithm.Firstly,the bad block management strategy based on parallel double-traverse mechanism was proposed by analyzing the characteristics of structure and operation for the NAND flash memory,the design ideas of the double traverse mechanism were described and its effectiveness was analyzed.Then,the error correction algorithm based on the shortened code RS(246,240) and RS(134,128) in the field GF(28) was proposed,and the encode/decode algorithm and corresponding circuits were given.Finally,the verification experiments on an image storage platform in the prototype machine for a space multi-spectral camera were carried out.The experimental results show that the bad block management strategy can fast and reliably dispose the bad block events,and the algorithm can identify the bad blocks in one system clock period.The error correction algorithm can correct 27 B error within the 2 KB/page with a encoder speed of 72.53 MBps and a decoder speed of 54.26 MBps.Proposed stratege effectively solve the problem of unreliable recording data in the NAND flash memory.

In order to solve the vignette phenomenon in the central visual field of the reflecting-mirror-jointed camera,the reasons of the vignette phenomenon were analyzed,and the vignette energy distribution mathematics model was obtained. The vignette energy distribution curve was got using the mathematics model with MATLAB. At the same time,considering the veiling glare of the joint reflecting mirrors and the CCD responding heterogeneity,the radicalization calibration experiment for the CCD camera was carried out. The vignette area was shown by the mathematics model,with function approach law to draft the compensation factor curve of each point in the vignette area,reaching the relation of the compensation factor and the brightness value. Handling the radicalization calibration image and the outfield image,the vignette phenomenon was solved very well.

In order to save the resource and improve the speed of wavelet transform's hardware realization,an effective 2-dimension wavelet transform hardware structure has been proposed.This structure used parallel pipeline architecture,each layer of wavelet transform processed by parallel while pixels processed by pipeline.And the structure can improve the speed of wavelet transform,save the on-chip and external memory resource.It had been tested on Xilinx SPARTEN-3 series FPGA by processing large image with size 1 024×2 048.Results showed the image processing speed could reach 80 Mpixel/s,meeting the real-time requirement.

A new digital differentiator-based demodulator in a zeroIF receiver for 2.4 GHz Zigbee applications is proposed. It receives the In-phase (I) and Quadrature-phase (Q) signals which are oversampled and quantized by a 4-bit ADC @ 8 MHz. Two one-order digital differentiators based on Taylor series, two multipliers and an adder are adopted to calculate the derivative of the signal phase. Then an Integrate-and-Dump Filter (IDF) is applied to obtain the phase difference in the chip time and determine its sign as the transmitted data. No complex carrier synchronization is needed and the demodulator can achieve low power consumption and low cost for its simple architecture. The theoretical analysis of Chip Error Rate (CER) under Additive White Gaussian Noise (AWGN) environment is also presented. The simulation results show that the proposed demodulator achieves Packet Error Rate (PER) of 1% with Carrier Frequency Offset (CFO) of 200 KHz and Signal-Noise Ratio (SNR) of 9.4 dB.

Wind power forecasting is one of the effective ways to mitigate the challenges for power system and wind farm owners. It is significant to make reliable prediction for the safety and stability of power system, the quality of electric power, and the increase of wind farm capacity coefficient. With good prediction and generalization abilities, relevance vector machine (RVM) is able to provide accurate single point prediction as well as additional probabilistic fluctuation information. However, traditional RVM based forecasting model is implemented with one kernel function. This impairs the forecasting adaptability for variable conditions and incurs mathematical solving problems. To solve this problem, this paper presents a hybrid RVM wind power probabilistic forecasting (WPPF) model with five kernel functions, which are Gaussian kernel, Laplacian kernel, Cauchy in distance kernel, R(distance) kernel, and Tps (Thin-plate spline) kernel. Besides, support vector machine forecasting with different kernels is also proposed to investigate the single kernel performance in machine learning forecasting. To take a wind farm in Eastern China as example, the adaptability and forecasting performance of each single kernel model are demonstrated. And, the proposed hybrid RVM model is proved to be capable of expanding the range of kernel parameter and have better adaptability and accuracy than those of a single kernel model.

In China, most directions of river flowing are from west to east. During historic period, since the water traffic played an important role, it was very important to form a cross-horizontal net of water carriage route. Canals should be dug so as to make up the lack of north-south river. Tongji Grand Canal, dug in the first year of Daye (605 A.D.) in the Sui Dynasty, was the important component of north-south system of Grand Canals in China. It promoted economic and social development of the Sui, Tang and Song dynasties (605 A.D.-1279 A.D.). As Tongji Canal (i.e.Tongji Grand Canal) flowed across the Huaibei Plain, which is aggraded by abundant mud and sand deposit resulted from the Huanghe (Yellow) River flooding, many traces (such as old channel) and human culture heritages were buried under mud-sand. Tongji Canal was silted up, and disappeared in the Jin Dynasty (1115 A.D.-1234 A.D.). From then on, there were many different stories about the flowing route of the canal in historical literature. Based on space-bone and air-bone remote sensing imagery, we attempt to search the old channel of Tongji Canal, and supplement historical record. The paper discusses transformation process of Tongji Canal's traffic function, and resumptively summarizes the reasons of the transformation, which results from synthetic function of physical geographical, political, economic, and social conditions.

Perforating globe injury is the leading cause of monocular blindness and vision loss. A 58-year-old male was injured by acupuncture needle during acupuncture treatment for his cerebral infarction. To the best of our knowledge, this is the first case report of perforating injury of the eyeball and traumatic cataract caused by acupuncture. The patient was hospitalized due to diagnosis of perforating ocular injury, traumatic cataract, and corneal and iris perforating injury. Moreover, he had to accept treatments of phacoemulsification, anterior vitrectomy along with intraocular lens implantation in the sulcus to improve his visual acuity. As acupuncture therapy has been widely performed for various diseases and achieved highly approval, the aim of this report is to remind acupuncturists operating accurately to avoid unnecessary injury during the treatment process, or the cure can also become the weapon.

Objective: To investigate cyclooxygenase- 2(Cox-2) protein expression in esophageal cancer and precancerous lesions. Methods: One hundred twenty biopsy specimens from esophageal carcinoma and 113 from patients with esophageal premalingnant lesions, 27 from individuals with normal esophageal mucosa and 3 from Barrett’s esophagus were examined for Cox-2 protein expression by immunohistochemistry. Results: Cox-2 protein was not observed in normal esophageal squamous and glandular epithelium, hyperplasia from mild to severe dysplasia lesions and carcinoma in situ. Positive Cox-2 protein expression was found in 4 of 60 specimens of invasive squamous-cell carcinomas, 21 of 30 specimens of esophageal adenocarcinomas and in 3 of 3 Barret’s esophageal tissues. Conclusion: The Cox-2 protein expression may be associated with the development of the esophageal adenocarcinomas but not esophageal squamous-cell carcinomas.

Wind power is fluctuate, intermittent and stochastic. The large capacity wind power connected with power grids will bring austere challenge to the safety and stabilization of power system operation. Wind speed prediction is an effective approach for this problem. ANN (artificial neural network) has been used extensively in wind speed prediction. But ANN is apt to getting into local minima and its convergence rate is slow. Tabu search is a kind of intelligent algorithm, which can achieve the global optimizations. This paper put forward a wind speed prediction model of neural network based on tabu search algorithm. How to decide the input of a neural network is a difficult issue. This paper put forward a simple linear correlation analysis method for the input selection. The result shows that with appropriate input parameters, the wind speed prediction model of neural network based on tabu search algorithm can improve the prediction precision.

In this paper, a novel impedance control method for high precision fuzzy controller with self adjustment quantitative factor is presented. This method can not only realize the real-time control by adjusting impedance parameters, but also enhance the stability and dynamic characteristics of the system. We have demonstrated this strategy is feasible and effective based on the simulation researches of free-form surfaces polishing robotic arm

In this paper, we present a new trace-tracking control algorithm, in which a self-regulation factor is adopted to realize real-time position control with high-precision fuzzy controller. The mover current is adjusted by given acceleration to implement real-time control and to enhance the characteristic of trajectory tracking in virtual-axis polishing machine. The experiment results demonstrate that high-precision real-time trajectory control of position, speed and acceleration in each link has attained and the static and dynamic characteristics of machine are enhanced.

In the test course of static transfer function of TDI CCD camera, because of the influence that gets environmental and artificial etc. factor, the value of static transfer function measured at any time is between unceasing fluctuation, so, make accuracy reduce. To solve this problem, a kind of accurate measurement technique of static transfer function is put forward. First, before carrying out the measure of static quiet of transfer function, the best test point of transfer function of the TDI CCD camera must be determined, it is parallel to guarantee the rectangle target surface of parallel optical pipe and camera focal plane maintenance parallel, and again guarantee target strip in rectangle target and TDI CCD in camera focal plane maintenance vertical. TDI CCD catches rectangle target image, per 1000 lines of target mark image as a measures sample of static transfer function, exclude because of atmosphere tremble twisted, vague rectangle target mark image, retain 500 distinct and steady target mark image as measure sample set. Then, calculate the static transfer function of each measure sample respectively, take the average of all static quiet transfer function in measure sample set as the static transfer function of camera. Finally, the measure of the static transfer function for TDI CCD camera makes error analysis. Experimental results indicate that the value of the static transfer function of TDI CCD camera measured with this kind of method is 0.2923, with before measurement technique comparison, the value of static transfer function has raised 0.02, makes the accuracy of the measure of static transfer function have gotten raising.