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.

Description: IJERPH, Vol. 14, Pages 1221: Nicotine Component of Cigarette Smoke Extract (CSE) Decreases the Cytotoxicity of CSE in BEAS-2B Cells Stably Expressing Human Cytochrome P450 2A13 International Journal of Environmental Research and Public Health doi: 10.3390/ijerph14101221 Authors: Minghui Ji Yudong Zhang Na Li Chao Wang Rong Xia Zhan Zhang Shou-Lin Wang Cytochrome P450 2A13 (CYP2A13), an extrahepatic enzyme mainly expressed in the human respiratory system, has been reported to mediate the metabolism and toxicity of cigarette smoke. We previously found that nicotine inhibited 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) metabolism by CYP2A13, but its influence on other components of cigarette smoke remains unclear. The nicotine component of cigarette smoke extract (CSE) was separated, purified, and identified using high-performance liquid chromatography (HPLC) and ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS), splitting CSE into a nicotine section (CSE-N) and nicotine-free section (CSE-O). Cell viability and apoptosis by Cell Counting Kit-8 (CCK-8) and flow cytometry assays were conducted on immortalized human bronchial epithelial (BEAS-2B) cells stably expressing CYP2A13 (B-2A13) or vector (B-V), respectively. Interestingly, CSE and CSE-O were toxic to BEAS-2B cells whereas CSE-N showed less cytotoxicity. CSE-O was more toxic to B-2A13 cells than to B-V cells (IC50 of 2.49% vs. 7.06%), which was flatted by 8-methoxypsoralen (8-MOP), a CYP inhibitor. CSE-O rather than CSE or CSE-N increased apoptosis of B-2A13 cells rather than B-V cells. Accordingly, compared to CSE-N and CSE, CSE-O significantly changed the expression of three pairs of pro- and anti-apoptotic proteins, Bcl-2 Associated X Protein/B cell lymphoma-2 (Bax/Bcl-2), Cleaved Poly (Adenosine Diphosphate-Ribose) Polymerase/Poly (Adenosine Diphosphate-Ribose) Polymerase (C-PARP/PARP), and C-caspase-3/caspase-3, in B-2A13 cells. In addition, recombination of CSE-N and CSE-O (CSE-O/N) showed similar cytotoxicity and apoptosis to the original CSE. These results demonstrate that the nicotine component decreases the metabolic activation of CYP2A13 to CSE and aids in understanding the critical role of CYP2A13 in human respiratory diseases caused by cigarette smoking.

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.

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.

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.

Description: This work presents a brief introduction on the basics of fiber-optical sensors and an overview focused on the applications to measurements in multiphase reactors. The most commonly principle utilized is laser back scattering, which is also the foundation for almost all current probes used in multiphase reactors. The fiber-optical probe techniques in two-phase reactors are more developed than those in three-phase reactors. There are many studies on the measurement of gas holdup using fiber-optical probes in three-phase fluidized beds, but negative interference of particles on probe function was less studied. The interactions between solids and probe tips were less studied because glass beads etc. were always used as the solid phase. The vision probes may be the most promising for simultaneous measurements of gas dispersion and solids suspension in three-phase reactors. Thus, the following techniques of the fiber-optical probes in multiphase reactors should be developed further: (1) online measuring techniques under nearly industrial operating conditions; (2) corresponding signal data processing techniques; (3) joint application with other measuring techniques.

Description: Metal roof sheathings are widely employed in large-span buildings because of their light weight, high strength and corrosion resistance. However, their severe working environment may lead to deformation, leakage and wind-lift, etc. Thus, predicting these damages in advance and taking maintenance measures accordingly has become important to avoid economic losses and personal injuries. Conventionally, the health monitoring of metal roofs mainly relies on manual inspection, which unavoidably compromises the working efficiency and cannot diagnose and predict possible failures in time. Thus, we proposed a novel damage monitoring scheme implemented by laying bend sensors on vital points of metal roofs to precisely monitor the deformation in real time. A fast reconstruction model based on improved Levy-type solution is established to estimate the overall deflection distribution from the measured data. A standing seam metal roof under wind pressure is modeled as an elastic thin plate with a uniform load and symmetrical boundaries. The superposition method and Levy solution are adopted to obtain the analytical model that can converge quickly through simplifying an infinite series. The truncation error of this model is further analyzed. Simulation and experiments are carried out. They show that the proposed model is in reasonable agreement with the experimental results.

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.

Description: Sensors, Vol. 18, Pages 660: Enhanced Humidity Sensitivity with Silicon Nanopillar Array by UV Light Sensors doi: 10.3390/s18020660 Authors: Wei Li Chao Ding Yun Cai Juyan Liu Linlin Wang Qingying Ren Jie Xu The sensitivity of silicon nanopillar array for relative humidity (RH) with UV illumination was investigated in this work. The silicon nanopillar array was prepared by nanosphere lithography. Electrical measurements were performed on its sensing performance with and without UV irradiation. It was found that UV light improved the humidity sensitivity with different UV light wavelengths and power. The sensor response and recovery time were reduced. Furthermore, the turn-on threshold voltage and the operating voltage both decreased. These sensing characteristics can mainly be attributed to the electron-hole pairs generated by UV light. These electron-hole pairs promote the adsorption and desorption processes. The results indicate that silicon nanopillar array materials with UV irradiation might be competitive as novel sensing materials for fabricating humidity sensors with high performances.

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.