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Dihydromyricetin up-regulated MyHC I expression and down-regulated MyHC IIb expression via AMPK signal in porcine myotubes.

Dihydromyricetin improves meat quality and promotes skeletal muscle fiber type transformations from fast-twitch to slow-twitch via AMPK signaling in growing–finishing pigs.

This study aimed to investigate the effect of dietary dihydromyricetin (DHM) supplementation on lipid metabolism, antioxidant capacity and muscle fiber type transformation. Twenty-four male Kunming mice were randomly allotted to either control (basal diet) or DHM diets (supplemented with 300 mg/kg DHM). Our data showed that DHM administration decreased the triglycerides (TG) and low-density lipoprotein cholesterol (LDL-C) contents, and increased the catalase (CAT), total superoxide dismutase (T-SOD) and glutathione peroxidase (GSH-Px) activities in serum. In the liver, DHM decreased the TG and malondialdehyde (MDA) levels and increased the T-SOD and GSH-Px activities. For the tibialis anterior (TA) muscle, DHM increased the total antioxidant capacity (T-AOC) level and T-SOD activities. Western blotting and real-time quantitative PCR analysis showed that DHM increased the protein and mRNA levels of MyHC I and MyHC IIa and decreased the protein and mRNA levels of MyHC IIb in TA muscle, which may be achieved by activating the AMP-activated protein kinase (AMPK) signal. The mRNA levels of several regulatory factors related to mitochondrial function were up-regulated by DHM. In conclusion, dietary 300 mg/kg DHM supplementation improved lipid metabolism and antioxidant capacity and promoted the transformation of muscle fiber type from glycolysis to oxidation in mice.

Thirty castrated Duroc × Landrace × Yorkshire (DLY) pigs were randomly divided into three groups and slaughtered at 180, 210, and 240 days of age, respectively. Here, we found that the live weight, carcass weight, carcass length, dressing percentage, eye muscle area, backfat deposit, muscle yellowness b* value, drip loss, and cooking loss increased significantly, and the muscle pH 45 min value decreased dramatically as the slaughter age of DLY pigs extended. Moreover, increasing the slaughter age of DLY pigs could obtain higher n-3 polyunsaturated fatty acid (PUFA) percentage, crude protein, essential amino acids (EAA) contents and EAA/NEAA level, and lower n-6/n-3 PUFA level and antioxidant capacity. Together, this study suggests that the older slaughter age improves the carcass traits and nutritional value of pork, but leads to a significant decrease in pork sensory quality in DLY finishing pigs.

Air pollution has emerged as one of the most urgent problems worldwide over the past few years. Especially, fine particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) has seriously endangered the human life and health worldwide. Thus, monitoring accurate and spatio-temporal continuously PM2.5 concentrations is essential for controlling air pollution. The key to accurately estimating PM2.5 concentrations is to build a reliable aerosol optical depth (AOD)–PM2.5 model, which is mainly determined by the AOD remotely sensed products, meteorological parameters, and estimating methods. However, no systematic evaluation and analysis of the influence of these three variables on AOD–PM2.5 model has yet been reported. Based on Terra and Aqua Moderate Resolution Imaging Spectroradiometer AOD products, reanalysis meteorological data, and ground-based PM2.5 data during 2014–2015 in eastern China, we analyzed the influence of above mentioned variables on the accuracy of the AOD–PM2.5 model. The four modeling methods investigated are stepwise multiple linear regression (SMLR), backpropagation neural network (BPNN), classification and regression tree (CART), and random forest (RF). Adjusted R2, mean absolute error (MAE), product index (PI), spatial resolution index (SRI), and Taylor diagrams are used to assess the accuracy of models. The results show that adding meteorological elements that vary with time and height can improve the accuracy by 4.97% over eastern China. The average PI of Terra AOD products increased by 0.15 compared with that of Aqua AOD products. Most SRIs have positive values, suggesting that AOD products with a spatial resolution of 10 km can lead to a more accurate AOD–PM2.5 model. The Taylor diagram indicates that RF model > BPNN model > CART model > SMLR model in terms of performance. Therefore, Terra AOD products with spatial resolution of 10 km and RF are more suitable for use with the AOD–PM2.5 model in eastern China.

This study aimed to examine the effects of apple polyphenols (APPs) on antioxidant capacity, immune and inflammatory response, and barrier function in weaning piglets. Results showed that APPs improved jejunal barrier function by increasing the villus height, villus height/crypt depth, the mRNA levels of occludin, mucin-1, and mucin-4 and up-regulating the protein expression of occluding (P 0.05). As for antioxidant capacity, APPs increased the activities of total superoxide dismutase and glutathione peroxidase and total antioxidant capacity level in jejunum (P 0.05). Besides, APPs up-regulated the protein expressions of NAD(P)H quinone dehydrogenase 1 (NQO1), heme oxygenase-1 (HO-1), and nuclear-related factor 2 (NRF2) and down-regulated the protein expression of kelch-like ECH-associated protein 1 (Keap1). As regard to immune and inflammatory response, APPs increased the immunoglobulin A content in serum and decreased the mRNA levels of tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, toll-like receptor 4 (TLR4), nuclear factor-κB (NF-κB), and IL-8 in jejunum (P 0.05). Overall, dietary APPs supplementation improves the jejunal barrier function by enhancing antioxidant capacity and suppressing the mRNA expression related to inflammation, which may be related to the NRF2 signal and TLR4/NF-κB signal.

Accurate spatial distribution information on gross domestic product (GDP) is of great importance for the analysis of economic development, industrial distribution and urbanization processes. Traditional administrative unit-based GDP statistics cannot depict the detailed spatial differences in GDP within each administrative unit. This paper presents a study of GDP spatialization in Ningbo City, China based on National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL) data and town-level GDP statistical data. The Landsat image, land cover, road network and topographic data were also employed as auxiliary data to derive independent variables for GDP modelling. Multivariate linear regression (MLR) and random forest (RF) regression were used to estimate GDP at the town scale and were assessed by cross-validation. The results show that the RF model achieved significantly higher accuracy, with a mean absolute error (MAE) of 109.46 million China Yuan (CNY)·km−2 and a determinate coefficient (R2 = 0.77) than the MLR model (MAE = 161.8 million CNY·km−2, R2 = 0.59). Meanwhile, by comparing with the estimated GDP data at the county level, the town-level estimated data showed a better performance in mapping GDP distribution (MAE decreased from 115.1 million CNY·km−2 to 74.8 million CNY·km−2). Among all of the independent variables, NTL, land surface temperature (Ts) and plot ratio (PR) showed higher impacts on the GDP estimation accuracy than the other variables. The GDP density map generated by the RF model depicted the detailed spatial distribution of the economy in Ningbo City. By interpreting the spatial distribution of the GDP, we found that the GDP of Ningbo was high in the northeast and low in the southwest and formed continuous clusters in the north. In addition, the GDP of Ningbo also gradually decreased from the urban centre to its surrounding areas. The produced GDP map provides a good reference for the future urban planning and socio-economic development strategies.

Nowadays, chronic diseases have become a potential danger to human health and are highly concerning. Given that pigs are a suitable animal model for human nutrition and metabolism for its similar anatomical and physiological properties to those of humans, this study has used 24 castrated male Duroc × Landrace × Yorkshire (DLY) pigs as experimental subjects to explore the effects of dietary dihydromyricetin (DHM) supplementation on the antioxidant capacity and lipid metabolism. Results showed that dietary 300 and 500 mg DHM kg-1 diet supplementation increased the serum total superoxide dismutase (T-SOD) level, serum and liver reduced glutathione (GSH), muscle catalase (CAT) level and serum high-density lipoprotein cholesterol (HDL-C) level, and reduced the liver malondialdehyde (MDA) level and muscle triglyceride (TG) level in finishing pigs. Western blot analysis showed that dietary DHM supplementation activated the nuclear-related factor 2 (Nrf2) and AMP-activated protein kinase (AMPK)/acetyl-CoA carboxylase (ACC) signals. Real-time quantitative PCR analysis showed that dietary DHM supplementation upregulated the mRNA levels of lipolysis and fatty acid oxidation-related genes, and down-regulated the mRNA expression of lipogenesis-related genes in finishing pigs. Together, we provide evidence that dietary DHM supplementation improved the antioxidant capacity and lipid metabolism in finishing pigs.

Urbanization has led to an obvious urban heat island (UHI) effect in the Yangtze River Delta (YRD), China. The ozone (O3) pollution in the YRD is getting worse. The UHI effect is a key factor that affects the O3 level. Understanding the influences of the UHI effect on O3 concentrations is necessary for improving air quality. In this study, the temporal and spatial relationship between UHI and O3 in the YRD during 2015 was investigated. The influence factors of UHI effect and O3 are both natural and artificial. Multi-source remote sensing data, which include land cover, land surface temperature (LST), Normalization Difference Vegetation Index (NDVI), and digital elevation model (DEM) data, were used to extract surface landscape elements. The results showed that: (1) the average hourly O3 concentration was 61.83 μg/m3 (30.92 ppb), the highest value was 105.32 μg/m3 (52.66 ppb) at 15:00 and the O3 peak was 82.50 μg/m3 (41.25 ppb) in September. The O3 concentrations and temperature have a similar variation trend both in diurnal and monthly. The O3 concentrations in coastal stations are higher than those inland. (2) The average daytime UHI intensity was 1.24 °C, and the daytime O3 concentration was 80.66 μg/m3 (40.33 ppb). There is a positive relationship between UHI and O3 in the YRD. The relationship in the central developed cities is higher than that in the northern and southern cities. (3) The related factors influencing UHI and O3 include surface landscape, topography and population. The LST and NDVI are most important among these factors. (4) Due to various geographical backgrounds, the UHI intensities and O3 concentrations show obvious spatial differences. This study provides a reference with which to better understand the relationship among UHI, O3 and related factors. Furthermore, the issues of atmospheric and energy transmission in this region deserve further study.

Aerosol can induce visibility reduction, affect radiation balance and modify cloud property on the environmental effect, and show the harmful effects on human health. Insight of aerosol becomes an integral task in the process of control measures for environmental pollution. The present study provided an analysis of temporal–spatial variations of aerosol optical depth (AOD) using the MOD04 level-2 in collection 6 (C6) with the deep blue retrieval algorithm from January 2005 to December 2015 over Yangtze River Delta (YRD) in China. The AOD validations between MODIS and Aerosol Robotic Network (AERONET) were estimated by the methods of regression, correlation. Then, the periodic features and trends of AOD and angstrom exponent (AE) were explored with the wavelet transformation (WT) procedure. Further, the variations of AOD and AE spatial distribution on multi-time scales (annual, monthly and season) were demonstrated. Meantime, the sources of AOD are discussed. It was found that the daily AOD from MODIS has a strong correlation relationship (slope = 0.9838, r = 0.84) with AERONET over YRD. The variations of both AOD and AE on time series have been distinct temporal periodic (12, 6 and 4 months) characteristics, and show the decreasing trends on annual and semi-annual periods. On annual, the AOD on spatial distribution is slowly declining from the northwest towards the southeast, and the AE on spatial distribution is gradually decreasing from the northwest to the southeast and from the land to the coast. The variations both inter-annual AOD and AE on spatial distribution show the inverse trends, respectively. On monthly, the means of AOD range from minimum 0.46 in January to maximum 0.90 in July, and the variations of spatial distribution mainly occur in the north parts of Yangtze River and some scattered areas with high terrain and south coast. The means of AE range from minimum 1.13 in October to maximum 1.58 in April, and the variations of spatial distribution are mainly found in the south of Henan, the north of Jiangsu, the coast belt and the riverside of Yangtze River and the high terrain regions. On seasonality, the means of AOD reaches its maximum 0.68 in summer and minimum 0.50 in winter, and the variations of spatial distribution mainly occur in the coast belt, the north parts of Hongze Lake and the south parts with high terrain. The means of AE reaches its maximum 1.48 in spring and minimum 1.25 in autumn, and the variations of spatial distribution were shown the similarity with that of monthly.

The acceleration of the industrialization process in China has increased the demand for electricity and triggered a power-plant building boom, especially along China’s eastern coast, where the economy gets off early and enjoys a fast development. The thermal plumes, residual chlorine, nuclides and other pollutions produced by the thermal and nuclear power plants have exerted an impact on the coastal eco-environment. To monitor the thermal pollution from the power plants at Yueqing Bay on the eastern coast, in this research, the distribution of sea surface temperature (SST) surrounding the power plants is obtained by using the SST retrieval methods developed for Landsat Enhanced Thematic Mapper Plus (ETM+), HJ-1B infrared sensor (IRS) and Terra moderate resolution imaging spectroradiometer (MODIS) data. The comparison of the SST retrieval results before and after the operation of power plants indicates that the total area of sea waters that is impacted by the thermal discharge from the two power plants at Yueqing Bay is approximately 17.95 km2, with the highest SST rise of 4.5 °C appearing over the waters around the outlet of the Huaneng Yuhuan power plant on the eastern shore, whereas the highest SST rise around the Zheneng Yueqing power plant on the western shore reaches 3.8 °C. The intensity and scope of influence of the thermal discharge mainly depend on the installed capacity of power plants, coastal terrain, and tide. Although the area where the SST rise is more than 3 °C is not large, thermal discharge still has an impact on bay ecosystems due to the relatively closed nature of the bay environment. Due to the influence of rising water temperatures on the reproduction and individual evolution of fish, shrimp, crabs, shellfish and other aquatic creatures, in the long term, the thermal pollution from coastal power plants will affect the volume of natural fishery and biological resources throughout the waters. The quantitative retrieval results also suggest that relative to MODIS data, Landsat ETM+ and HJ-1B IRS data with a high spatial resolution are more applicable to the estimation of small-scale SST, and IRS data with a high temporal resolution are more helpful in the study of spatio-temporal variability of thermal plumes from coastal power plants.

As a comprehensive capacity of nature, society and humans, integrated carrying capacity (ICC) is the driving force of regional socioeconomic development. Only when an ecosystem is under-loaded can socioeconomic development be sustainable. ICC is an accumulative total value of each indicator's carrying capacity, which reflects a static status. The ICC prediction analysis is one prerequisite to making economic development plans. In this paper, a dynamic prediction model is developed by using the model of set pair analysis (SPA) to predict the growth tendency of ICC. The model is tested in a case comprising eight coastal cities in Yangtze. (1) The average error rate of this prediction model is merely 0.38%, and the lowest error rate is 0.01%. The SPA model is better to predict ICC tendencies. (2) According to the national development plan, the eight cities' ICC is predicted in 2015. (3) The prediction model is a multiple method that can contain all indicators of ICC. This model can estimate the maximal carrying capacity of a natural ecosystem to make the most suitable economic development policy. The socioeconomic development must comply with the under-loaded capacity to maintain sustainable development.

In this paper, we propose a model based on the bag of mixed-gram terms to deal with sentiment classification task and extracting sentimental features. We obtain a very short-dimensional vector to represent sentiment and use the sentimental representations to complete the task of sentiment classification. Furthermore, since the sentimental representations and some traditional word vectors have complementary advantages, we combine the sentimental representations with convolutional neural networks that use other word vectors and ultimately implement a more efficient classifier. Experimental results show that this combination method can use static word vectors to deal with sentimental classification tasks well, and the sentimental representations here play the role of fine-turned word vectors in previous research.

As an indispensable homestead, the ecosystem witnesses a large number of human activities. Undoubtedly, socio-economic development consumes a variety of natural resources and causes stress to the ecosystem. Only when the ecosystem is in under-loading, socio-economic development can be sustainable. In this paper, the integrated carrying capacity (ICC), which is a comprehensive capacity measure, is calculated in given space and time frames to support the evaluation of long-term sustainable regional economic development. Combined with the conceptual mode of “ driving force – pressure – state – response – control ” (D–PSR–C), the ICC reveals the loading capacity between human activity and the ecosystem. In coastal zones, the ICC is more effective because of the rapid socio-economic development. Using a case study in the Nantong coastal area in China, we constructed an index system to assess the regional ICC and its variability in 2005, 2008 and 2009. The results indicate that (1) almost all county ICC states of land, shoals, marine and regional are under-loading with several exceptions that are full-loading. The highest value is the regional ICC of Qidong in 2009 (2.679 and under-loading). The lowest value is the Haian marine ICC in 2008 (0.171 and over-loading). (2) From 2005 to 2009, the ICC values of beach, marine and regional were increasing, but it was decreasing in land. (3) Based on the analysis of the carrying capacity of the secondary indicator contribution rate, the population pressure and the external contribution ability are nearly below 10%, and environmental pollution is also a critical indicator. In this paper, the assessment indices system contains almost all of the impacts of human activity, and the calculation method and the judgment standard can improve the traditional method's faultiness. The conclusions are a fundamental basis for the long-term balance between economic development and ecosystem health.

While the development of social economy in the coastal areas, the demand of electricity is rising up and the construction of coastal power station is accelerating, but the discharge water is increasingly serious damage to the coastal sea. This paper introduces the system framework and the main function, which is based on GIS to monitor and evaluate the discharge water of power station, and divide the damage rank by using RS, monitoring analysis and discharge standard, so that we can calculate the compensation total value by using ecological compensating technology and draft the management program of the power station. The system can achieve the auto management of the power station, which can assure the normal working of power station and the health of eco-environment to balance the development of the economy and the eco-system.

To reduce typhoon-caused damages, numerical and empirical methods are often used to forecast typhoon storm surge. However, typhoon surge is a complex nonlinear process that is difficult to forecast accurately. We applied a principal component back-propagation neural network (PCBPNN) to predict the deviation in typhoon storm surge, in which data of the typhoon, upstream flood, and historical case studies were involved. With principal component analysis, 15 input factors were reduced to five principal components, and the application of the model was improved. Observation data from Huangpu Park in Shanghai, China were used to test the feasibility of the model. The results indicate that the model is capable of predicting a 12-hour warning before a typhoon surge.

The thermal plume discharged from the power plants has exerted many negative effects on the coastal environment by decreasing the dissolved oxygen, density and viscosity of water, speeding up the settlement of suspended mater, and changing the habit of life, growth and reproduction of marine organisms. To monitor the thermal pollution of cooling-water discharge from the coal-fired power plants and nuclear power plant in the eastern coastal region in China, the mono-window algorithm for retrieving sea surface temperature (SST) from thermal infrared bands of Landsat TM/ETM+, and HJ IRS data is improved by integrating the atmospheric correction model. The SST variability influenced by the thermal discharge from the coal-fired power plants and nuclear power plant near Xiangshan Harbour, Tianwan and Yueqing Bay in the eastern coastal area in China is investigated by comparing the distributions of SST around the power plants before and after the operation of the power plants. The results indicate that the spatial variability of SST rise depends on the installed capacity of power plants, coastal terrain, tide, etc. Although the area where the SST rise is more than 3°C was not large, thermal discharge still exerts impact on ecosystems within the bay to some degree due to the relatively closeness of the environment of the bay. Taking the coastal terrain near the power plants into consideration, more reasonable operation projects of the power plants and the design of the intake and discharge mouth should be set up in order to accelerate the dilution, diffusion and cooling of the thermal plume under the influence of discharged flow of the rivers, and reduce the impact of thermal pollution on the ecological community with high biodiversity in the intertidal zone.

Since a large proportion of pixels are often composed of mixed land cover types within remote sensing images, how to eliminate the impact of the error resulting from pixel mixing effect in the estimation of land surface emissivity on the accuracy of land surface temperature (LST) retrieval from remote sensing data is a key problem to resolve firstly in process of LST retrieval. Based on the local relationship between the thermal radiance of one pixel and that of its components satisfying the Planck's radiance function, in this paper, the mono-window algorithm was improved by integrating with mixed-pixel classification and sub-pixel mapping for Landsat imagery. Validation indicates that the improved mono-window algorithm is able to provide more accurate LST than the original algorithm for Landsat TM/ETM+ imagery. By applying the improved algorithm to the Landsat image of Shanghai, the result revealed the spatial heterogeneity characteristics of UHI effect in Shanghai city.

Thermal power technology has brought great convenience for human electricity energy demand, but thermal discharge from thermal power plants has caused great harm to the coastal environment. Therefore, it’s important to strengthen the monitoring of thermal pollution from power plants for guarantee the normal operation of coastal environment and ecological system. Thermal infrared remote sensing technology provides a new measure for monitoring the thermal discharge. In this paper, we use mono-window algorithm and Landsat thermal infrared data to retrieved the sea surface temperature around Xiangshan Power Plants, and achieved the result of 1~5.4°C temperature rise in 106.52km2 in Xiangshan Harbor, revealed the spatial distribution regularities of thermal discharge and discussed the influence of thermal discharge on costal environment.

In this paper, we demonstrate a testing method for characterization of microgyroscopes using a virtual rate-table, which uses a series of voltage signals to emulate the Coriolis force induced by the angular rate inputs to obtain the frequency response of the gyroscope. The proposed approach holds the following advantages: 1) it provides a convenient and efficient way to evaluate the scale factor and bandwidth of the gyroscope operating in either open-loop mode or closed-loop mode, the laborious debugging by frequently utilizing the real rate-table can be avoided; 2) it can easily identify the dynamic response to external angular rate, which is the control plant during the rebalance control design for the sense mode in a large frequency range, avoiding the performance limit of the ordinary rate-table; and 3) it can be used in a self-test for the microgyroscope system for the error calibration and malfunction checking. The method was applied to a decoupled z -axis gyroscope. The test results show that the measured scale factor and bandwidth are 30.2 mV/(deg/s) and 8.0 Hz by the virtual rate-table method, which are in close agreement with the conventional rate-table method, i.e., 31.0 mV/(deg/s) and 7.4 Hz. The static calibration with the virtual rate-table was also evaluated. The scale factors measured with the conventional rate-table method and the virtual rate-table method are 31.0 mV/(deg/s) and 30.1 mV/(deg/s) with R2 nonlinearity of 0.03% and 0.02%, respectively.

Although the vibration effect of micro-perforated panels (MPPs) in passive sound absorption systems has been considered in some studies, research into active systems remains to be accomplished. In this paper, theoretical and experimental studies of hybrid systems using finite flexible MPPs are presented. The impedance of the flexible MPP is derived using the modal analysis solution of the classical plate equation. Then absorption coefficients are predicted based on an electro-acoustic equivalent circuit model. A study of the absorption mechanism of the hybrid system shows that panel vibration can degrade the Helmholtz-resonance absorption performance and bring out panel-type absorption, especially increasing the cavity absorption in systems using impedance-matching conditions. Theoretical results show good agreement with the experiments. It can be seen that flexible the MPP has the potential to dissipate more energy and can be utilized to improve the absorption performance of the hybrid system by appropriately selecting parameters.

This paper presents a design method of force rebalance control for the sense mode of a micromachined vibratory gyroscope with multiobjective. The control strategy is mainly based on constraining sensitivity margin specifications via numerical optimization approach, which embeds the sense mode in a closed-loop system to possess more robust performance. This paper also provides a quantitative methodology of configuring the system parameters to realize the functional electrostatic force feedback control for the microgyroscope in the case of nonideal coupling and external angular disturbance. Theoretical results predicted by the control loop are shown to be in close agreement with the experimental results using a practical microgyroscope, which indicated a satisfactory performance of the proposed control algorithm. The maximums of the sensitivity function and complementary sensitivity function are measured to be 4.5 and 1 dB, resulting in GM ≥ 7.84 dB and PM ≥ 35°. The gyroscope achieves a scale factor of 7.1 mV/deg/s with nonlinearity of 0.2% which is improved by one order of magnitude compared with that of the open loop. The bandwidth is extended to about 98 Hz from 30 Hz in the open loop. The quadrature error and temperature stability of the scale factor are reduced from - 10.33 to -59.22 dB and from 4858 to 646 ppm/°C with the force rebalance control, respectively.

This paper proposed an effective approach for extending the bandwidth of MEMS vibratory gyroscope by employing the electrostatic force feedback control. The mathematical model for the bandwidth is established through the dynamic model of the gyroscope, which indicates that the bandwidth of the sensor depends on the difference between the resonant frequencies of the two working modes. The system bandwidth can be enlarged by utilizing electrostatic force rebalance control to null Coriolis force caused by external angular rate which can also improve the performance of the transient response. Simulation results forecast a satisfactory performance of the control system with suggested control method.

An acceleration latching switch with independent multi-contacts is presented in this paper. All the contacts and their beams are independent to the proof-mass so as to prevent the contacts from the impact resulting from the rebound or vibration of the proof-mass once the switch is latched. Moreover, multiple contacts are used in order to get highly reliable contact, to lower the contact resistance and to increase the maximum allowable current. The switch was fabricated by low-cost two-mask silicon on glass process and tested. The latching shock is 4500G and the response time is less than 0.1 ms. The contact resistance is no more than 5 Ω while the isolation resistance is more than 200 MΩ and the maximum allowable current is up to 100 mA.

Research into pixel unmixing in remote sensing imagery led to the development of soft classification methods. In this article, we propose a possibilistic c repulsive medoids (PCRMdd) clustering algorithm which attempts to find c repulsive medoids as a minimal solution of a particular objective function. The PCRMdd algorithm is applied to predict the proportion of each land use class within a single pixel, and generate a set of endmember fraction images. The clustering results obtained on multi-temporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+) images of Shanghai city in China reveal the spatio-temporal pattern of Shanghai land use evolvement and urban land spatial sprawl in course of urbanization from 1989 to 2002. The spatial pattern of land use transformation with urban renewal and expansion indicates the urban land use structure is gradually optimized during vigorous urban renewal and large-scale development of Pudong area, which will have an active influence on improving urban space landscape and enhancing the quality of the ecological environment. In addition, accuracy analysis demonstrates that PCRMdd represents a robust and effective tool for mixed-pixel classification on remote sensing imagery to obtain reliable soft classification results and endmember spectral information in a noisy environment.

In this paper, a silicon bulk micromachined lateral-axis tuning-fork gyroscope (TFG) with a decoupled comb drive and torsional sensing comb capacitors is presented. The novel driving comb capacitors are used to suppress the parasitic out-of-plane electrostatic force and, hence, can decouple the mechanical crosstalk from the sensing mode to the driving mode in a simple manner. The torsional sensing combs are designed to differentially sense the out-of-plane rotational moment and are arranged centroidally to be immune to fabrication imperfections for good linearity and electrostatic force balancing. The torsional sensing combs adopted in the TFG help to lower the air damping of the sensing mode while the driving mode of the gyroscope is dominated by slide-film air damping; hence, it can work even at atmospheric pressure. The process for this lateral-axis gyroscope can also be used to fabricate z-axis gyroscopes; therefore, low-cost miniature monolithic inertial measurement units can be realized without vacuum packaging. The TFG is tested at atmospheric pressure with a sensitivity of 17.8 mV/°/s and a nonlinearity of 0.6% in a full-scale range of 1000°/s. The bias stability is measured to be 0.05°/s (1 ?) in 30 min with an equivalent noise angular rate of 0.02°/s/Hz1/2.

In this paper, a doubly decoupled x-axis gyroscope with novel torsional sensing comb capacitors is presented. The doubly decoupled design is more efficient to suppress mechanical coupling of gyroscope. Both driving and sensing modes of the gyroscope are dominated by slide film air damping, therefore, it can work even at atmospheric pressure. Moreover, the sensing capacitors adopt asymmetrical comb fingers so that they can differentially detect out-of-plane torsional movements. The fabrication process of the gyroscope is compatible with z-axis gyroscope process, which makes it potential to realize low cost monolithic MIMU (miniature inertial measurement unit) without vacuum packaging. The gyroscope was fabricated and tested. The sensitivity is 22 mV/°/s while the nonlinearity is 2.19% at atmosphere. The noise floor is 0.02°/s/Hz1/2.

This paper introduces a novel algorithm for delineating mutually exclusive service areas of shelters which have finite capabilities to accommodate residents who are unevenly distributed in space. Minimizing the travel cost and keeping spatial continuity with capability constraint are the convergent objectives of this algorithm. The algorithm partitions an entire residential area into a number of spatial units to handle the unevenness of demand, and employs a shift insertion mechanism to reduce travel cost and to improve the spatial continuity of service areas. A series of experiments and scenarios has been conducted for the city of Memphis, USA, to validate the proposed algorithm. Comparative experiments under different constraints show that the proposed algorithm is a feasible solution for delineating service areas. Various application circumstances (for example, travel-cost calculation methods and the granularity of available demographic data) are discussed to evaluate the algorithm's feasibility. The proposed algorithm can be applied not only to delineating service areas of existing shelters but also to optimizing location allocation of new shelters or other facilities with similar characteristics.

Investigating the evolvement process of Mesoscale Convective Systems (MCSs) over the Tibetan Plateau using satellite remote sensing image sequence is a very important and effective method of forecasting heavy rainfall. This paper presents a spatial data mining approach, by which a possible heavy rainfall forecast can be made, based on MCS tracking using remote sensing satellite images. Firstly, an automatic method for object tracking from the satellite image sequence is proposed, aiming at identification of the qualified MCSs, their characteristics and their moving trajectories. Then, a novel two-phase spatial data mining framework is designed to enable the deduction of the correlations and causalities between MCS activities and possible heavy rainfall occurrences. The proposed approach proves to be capable of lifting the heavy burden of manual rainfall forecasting from the shoulders of meteorologists, by automatically analyzing and interpreting massive, meteorological remote sensing data sets to assist weather forecasting.

In this paper, Geostationary Meteorological Satellite (GMS) infrared black-body temperature (T bb) data from June to August 1998 are used to automatically track the activity of Mesoscale Convective System (MCS) over the Tibetan Plateau in China. Consequently, the features of MCS, such as area, intensity, life cycle, activity region and shape, are obtained. High Resolution Limited Area Analysis and Forecasting System (HLAFS) values provided by China National Meteorological Center are used to study the relationships between the MCS trajectories and their environmental physical field values, based on the distribution and trajectories of MCSs over the Tibetan Plateau. Favorable environmental physical field charts of influencing MCS movement out of the Tibetan Pleteau in different UTC (Universal Time Coordinate) are developed by using spatial data mining techniques at levels of 400hPa and 500hPa, respectively.