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  • 1
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    IJERPH, Vol. 11, Pages 3995-4006: Neurological Effects of Pesticide Use among Farmers in China (2014)
    MDPI Publishing
    Details
    Publication Date: 2014-04-15
    Description: The intensive use of pesticides has attracted great attention from the Chinese government. However, current regulations have had limited influence on their safe use. Although the acute neurologic effects of pesticides have been well documented, little is known about their cumulative effects. Knowledge of the impact of pesticides on health may convince farmers to minimize their use. We conducted a cross-sectional study in three provinces of China to evaluate the relationship between pesticide exposure and neurological dysfunction. Crop farmers were divided into two groups depending on their level of pesticide exposure. A total of 236 participants were assessed by questionnaire and neurological examination for symptoms and signs of neuropathy. Characteristics of neurologic dysfunction following cumulative low-level exposure were assessed with logistic regression analysis. Farmers exposed to high-level pesticide use had greater risk of developing sensations of numbness or prickling (odds ratio (OR) 2.62, 95% confidence interval (CI): 1.08–6.36). After adjusting for recent exposure, the risk of numbness or prickling symptoms (OR 2.55, 95% CI: 1.04–6.25) remained statistically significant. Loss of muscle strength and decreased deep tendon reflexes had OR > 2, however, this did not reach statistical significance. These findings suggest that overuse of pesticides increased risk of neurologic dysfunction among farmers, with somatosensory small fibers most likely affected. Measures that are more efficient should be taken to curb excessive use of pesticides.
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
    Published by MDPI Publishing
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  • 2
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    Sensors, Vol. 17, Pages 2829: A “Skylight” Simulator for HWIL Simulation of Hyperspectral Remote Sensing (2017)
    MDPI Publishing
    In: Sensors
    Details
    Publication Date: 2017-12-07
    Description: Sensors, Vol. 17, Pages 2829: A “Skylight” Simulator for HWIL Simulation of Hyperspectral Remote Sensing Sensors doi: 10.3390/s17122829 Authors: Huijie Zhao Bolun Cui Guorui Jia Xudong Li Chao Zhang Xinyang Zhang Even though digital simulation technology has been widely used in the last two decades, hardware-in-the-loop (HWIL) simulation is still an indispensable method for spectral uncertainty research of ground targets. However, previous facilities mainly focus on the simulation of panchromatic imaging. Therefore, neither the spectral nor the spatial performance is enough for hyperspectral simulation. To improve the accuracy of illumination simulation, a new dome-like skylight simulator is designed and developed to fit the spatial distribution and spectral characteristics of a real skylight for the wavelength from 350 nm to 2500 nm. The simulator’s performance was tested using a spectroradiometer with different accessories. The spatial uniformity is greater than 0.91. The spectral mismatch decreases to 1/243 of the spectral mismatch of the Imagery Simulation Facility (ISF). The spatial distribution of radiance can be adjusted, and the accuracy of the adjustment is greater than 0.895. The ability of the skylight simulator is also demonstrated by comparing radiometric quantities measured in the skylight simulator with those in a real skylight in Beijing.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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  • 3
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    Sustainability, Vol. 10, Pages 1505: Re-Examining Embodied SO2 and CO2 Emissions in China (2018)
    MDPI Publishing
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    Publication Date: 2018-05-11
    Description: Sustainability, Vol. 10, Pages 1505: Re-Examining Embodied SO2 and CO2 Emissions in China Sustainability doi: 10.3390/su10051505 Authors: Rui Huang Klaus Hubacek Kuishuang Feng Xiaojie Li Chao Zhang CO2 and SO2, while having different environmental impacts, are both linked to the burning of fossil fuels. Research on joint patterns of CO2 emissions and SO2 emissions may provide useful information for decision-makers to reduce these emissions effectively. This study analyzes both CO2 emissions and SO2 emissions embodied in interprovincial trade in 2007 and 2010 using multi-regional input–output analysis. Backward and forward linkage analysis shows that Production and Supply of Electric Power and Steam, Non-metal Mineral Products, and Metal Smelting and Pressing are key sectors for mitigating SO2 and CO2 emissions along the national supply chain. The total SO2 emissions and CO2 emissions of these sectors accounted for 81% and 76% of the total national SO2 emissions and CO2 emissions, respectively.
    Electronic ISSN: 2071-1050
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI Publishing
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  • 4
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    Atmosphere, Vol. 9, Pages 5: Spatiotemporal Variations in Satellite-Based Formaldehyde (HCHO) in the Beijing-Tianjin-Hebei Region in China from 2005 to 2015 (2018)
    MDPI Publishing
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    Publication Date: 2018-01-02
    Description: Atmosphere, Vol. 9, Pages 5: Spatiotemporal Variations in Satellite-Based Formaldehyde (HCHO) in the Beijing-Tianjin-Hebei Region in China from 2005 to 2015 Atmosphere doi: 10.3390/atmos9010005 Authors: Songyan Zhu Xiaoying Li Chao Yu Hongmei Wang Yapeng Wang Jing Miao The widespread distribution and strong seasonal pattern of highly concentrated summertime formaldehyde (HCHO) were observed using data from the Ozone Monitoring Instrument (OMI) onboard Aura satellite from 2005 to 2015 in Beijing-Tianjin-Hebei, China. The large-scale HCHO concentrations and its close connection with the surface O3 pollution made the study of summertime HCHO patterns and its major contributors necessary. Accordingly, time series decomposition, Moran’s I and Pearson correlation coefficient (PCC) were adopted to investigate the spatiotemporal variations of HCHO. We found that the HCHO columns regionally increased from 2005 to 2010 and decreased in the north (e.g., Chengde) from 2010 to 2015. Additionally, HCHO Vertical Column Densities (VCDs) exhibited higher values in urban areas. Despite the strong possibilities of major biogenic contributions, anthropogenic sources represented larger spatial PCCs and larger total emission rates. Industrial sources exhibited a large increasing emission amount, and the most similar distribution to HCHO was found in residential sources. By comparison, power-based emissions accounted for a relatively small fraction, and transportation emissions declined rapidly. In conclusion, anthropogenic VOCs might contribute to the summertime HCHO concentrations as well as isoprene, and controls on VOCs and HCHO would be greatly assisted by the satellite-based observations.
    Electronic ISSN: 2073-4433
    Topics: Geosciences
    Published by MDPI Publishing
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  • 5
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    Sensors, Vol. 17, Pages 2769: An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification (2017)
    MDPI Publishing
    In: Sensors
    Details
    Publication Date: 2017-11-30
    Description: Sensors, Vol. 17, Pages 2769: An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification Sensors doi: 10.3390/s17122769 Authors: Fangmin Li Chao Yang Yuqing Xia Xiaolin Ma Tao Zhang Zhou Zhou In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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  • 6
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    IJGI, Vol. 6, Pages 364: Multiple Feature Hashing Learning for Large-Scale Remote Sensing Image Retrieval (2017)
    MDPI Publishing
    Details
    Publication Date: 2017-11-17
    Description: IJGI, Vol. 6, Pages 364: Multiple Feature Hashing Learning for Large-Scale Remote Sensing Image Retrieval ISPRS International Journal of Geo-Information doi: 10.3390/ijgi6110364 Authors: Dongjie Ye Yansheng Li Chao Tao Xunwei Xie Xiang Wang Driven by the urgent demand of remote sensing big data management and knowledge discovery, large-scale remote sensing image retrieval (LSRSIR) has attracted more and more attention. As is well known, hashing learning has played an important role in coping with big data mining problems. In the literature, several hashing learning methods have been proposed to address LSRSIR. Until now, existing LSRSIR methods take only one type of feature descriptor as the input of hashing learning methods and ignore the complementary effects of multiple features, which may represent remote sensing images from different aspects. Different from the existing LSRSIR methods, this paper proposes a flexible multiple-feature hashing learning framework for LSRSIR, which takes multiple complementary features as the input and learns the hybrid feature mapping function, which projects multiple features of the remote sensing image to the low-dimensional binary (i.e., compact) feature representation. Furthermore, the compact feature representations can be directly utilized in LSRSIR with the aid of the hamming distance metric. In order to show the superiority of the proposed multiple feature hashing learning method, we compare the proposed approach with the existing methods on two publicly available large-scale remote sensing image datasets. Extensive experiments demonstrate that the proposed approach can significantly outperform the state-of-the-art approaches.
    Electronic ISSN: 2220-9964
    Topics: Architecture, Civil Engineering, Surveying , Geosciences
    Published by MDPI Publishing on behalf of International Society for Photogrammetry and Remote Sensing (ISPRS).
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  • 7
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    IJGI, Vol. 6, Pages 377: A Virtual Geographic Environment for Debris Flow Risk Analysis in Residential Areas (2017)
    MDPI Publishing
    Details
    Publication Date: 2017-11-23
    Description: IJGI, Vol. 6, Pages 377: A Virtual Geographic Environment for Debris Flow Risk Analysis in Residential Areas ISPRS International Journal of Geo-Information doi: 10.3390/ijgi6110377 Authors: Lingzhi Yin Jun Zhu Yi Li Chao Zeng Qing Zhu Hua Qi Mingwei Liu Weilian Li Zhenyu Cao Weijun Yang Pengcheng Zhang Emergency risk assessment of debris flows in residential areas is of great significance for disaster prevention and reduction, but the assessment has disadvantages, such as a low numerical simulation efficiency and poor capabilities of risk assessment and geographic knowledge sharing. Thus, this paper focuses on the construction of a VGE (virtual geographic environment) system that provides an efficient tool to support the rapid risk analysis of debris flow disasters. The numerical simulation, risk analysis, and 3D (three-dimensional) dynamic visualization of debris flow disasters were tightly integrated into the VGE system. Key technologies, including quantitative risk assessment, multiscale parallel optimization, and visual representation of disaster information, were discussed in detail. The Qipan gully in Wenchuan County, Sichuan Province, China, was selected as the case area, and a prototype system was developed. According to the multiscale parallel optimization experiments, a suitable scale was chosen for the numerical simulation of debris flow disasters. The computational efficiency of one simulation step was 5 ms (milliseconds), and the rendering efficiency was approximately 40 fps (frames per second). Information about the risk area, risk population, and risk roads under different conditions can be quickly obtained. The experimental results show that our approach can support real-time interactive analyses and can be used to share and publish geographic knowledge.
    Electronic ISSN: 2220-9964
    Topics: Architecture, Civil Engineering, Surveying , Geosciences
    Published by MDPI Publishing on behalf of International Society for Photogrammetry and Remote Sensing (ISPRS).
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  • 8
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    Energies, Vol. 11, Pages 657: A Novel Direct Torque Control Method Based on Asymmetric Boundary Layer Sliding Mode Control for PMSM (2018)
    MDPI Publishing
    In: Energies
    Details
    Publication Date: 2018-03-16
    Description: Energies, Vol. 11, Pages 657: A Novel Direct Torque Control Method Based on Asymmetric Boundary Layer Sliding Mode Control for PMSM Energies doi: 10.3390/en11030657 Authors: Qiang Song Yiting Li Chao Jia A novel direct torque control (DTC) method based on sliding-mode-control (SMC) strategy is proposed for permanent magnet synchronous motor (PMSM) which is used in electric vehicles (EVs). In order to improve the dynamic response time and enhance the robustness performance against the external loading disturbances and motor parameter’s variation, a kind of SMC-based torque controller and speed controller are designed to regulate the torque angle increment and the speed respectively. The torque controller is designed based on a sliding mode controller with an asymmetric boundary layer to reduce the overshoot. Compared with other DTC methods based on space vector modulation (SVM) in the literature, the proposed DTC scheme adopts the asymmetric boundary layer SMC instead of the proportional-integral (PI) regulator. The simulation results have validated the effectiveness of the proposed SMC-based DTC method.
    Electronic ISSN: 1996-1073
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI Publishing
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  • 9
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    Sensors, Vol. 18, Pages 1217: Glucose Sensor Using U-Shaped Optical Fiber Probe with Gold Nanoparticles and Glucose Oxidase (2018)
    MDPI Publishing
    In: Sensors
    Details
    Publication Date: 2018-04-17
    Description: Sensors, Vol. 18, Pages 1217: Glucose Sensor Using U-Shaped Optical Fiber Probe with Gold Nanoparticles and Glucose Oxidase Sensors doi: 10.3390/s18041217 Authors: Kuan-Chieh Chen Yu-Le Li Chao-Wei Wu Chia-Chin Chiang In this study, we proposed a U-shaped optical fiber probe fabricated using a flame heating method. The probe was packaged in glass tube to reduce human factors during experimental testing of the probe as a glucose sensor. The U-shaped fiber probe was found to have high sensitivity in detecting the very small molecule. When the sensor was dipped in solutions with different refractive indexes, its wavelength or transmission loss changed. We used electrostatic self-assembly to bond gold nanoparticles and glucose oxidase (GOD) onto the sensor’s surface. The results over five cycles of the experiment showed that, as the glucose concentration increased, the refractive index of the sensor decreased and its spectrum wavelength shifted. The best wavelength sensitivity was 2.899 nm/%, and the linearity was 0.9771. The best transmission loss sensitivity was 5.101 dB/%, and the linearity was 0.9734. Therefore, the proposed U-shaped optical fiber probe with gold nanoparticles and GOD has good potential for use as a blood sugar sensor in the future.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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  • 10
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    Sensors, Vol. 17, Pages 1407: Dynamic Resource Allocation and Access Class Barring Scheme for Delay-Sensitive Devices in Machine to Machin (M2M) Communnications (2017)
    MDPI Publishing
    In: Sensors
    Details
    Publication Date: 2017-06-16
    Description: Supporting simultaneous access of machine-type devices is a critical challenge in machine-to-machine (M2M) communications. In this paper, we propose an optimal scheme to dynamically adjust the Access Class Barring (ACB) factor and the number of random access channel (RACH) resources for clustered machine-to-machine (M2M) communications, in which Delay-Sensitive (DS) devices coexist with Delay-Tolerant (DT) ones. In M2M communications, since delay-sensitive devices share random access resources with delay-tolerant devices, reducing the resources consumed by delay-sensitive devices means that there will be more resources available to delay-tolerant ones. Our goal is to optimize the random access scheme, which can not only satisfy the requirements of delay-sensitive devices, but also take the communication quality of delay-tolerant ones into consideration. We discuss this problem from the perspective of delay-sensitive services by adjusting the resource allocation and ACB scheme for these devices dynamically. Simulation results show that our proposed scheme realizes good performance in satisfying the delay-sensitive services as well as increasing the utilization rate of the random access resources allocated to them.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
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