Beschreibung: Individuals afflicted with occupational formaldehyde (FA) exposure often suffer from abnormal behaviors such as aggression, depression, anxiety, sleep disorders, and in particular, cognitive impairments. Coincidentally, clinical patients with melatonin (MT) deficiency also complain of cognitive problems associated with the above mental disorders. Whether and how FA affects endogenous MT metabolism and induces cognitive decline need to be elucidated. To mimic occupational FA exposure environment, 16 healthy adult male mice were exposed to gaseous FA (3 mg/m3) for 7 consecutive days. Results showed that FA exposure impaired spatial memory associated with hippocampal neuronal death. Biochemical analysis revealed that FA exposure elicited an intensive oxidative stress by reducing systemic glutathione levels, in particular, decreasing brain MT concentrations. Inversely, intraperitoneal injection of MT markedly attenuated FA-induced hippocampal neuronal death, restored brain MT levels, and reversed memory decline. At tissue levels, injection of FA into the hippocampus distinctly reduced brain MT concentrations. Furthermore, at cellular and molecular levels, we found that FA directly inactivated MT in vitro and in vivo. These findings suggest that MT supplementation contributes to the rescue of cognitive decline, and may alleviate mental disorders in the occupational FA-exposed human populations.

Beschreibung: Latent heat thermal energy storage (TES) plays an important role in the advocation of TES in contrast to sensible energy storage because of the large storage energy densities per unit mass/volume possible at a nearly constant thermal energy. In the current study, a heat exchange device with a zigzag configuration containing multiple phase-change-materials (m-PCMs) was considered, and an experimental system was built to validate the model for a single PCM. A two-dimensional numerical model was developed using the ANSYS Fluent 14.0 software program. The energy fractions method was put forward to calculate the average Ste number and the influence of Re and Ste numbers on the discharge process were studied. The influence of phase change temperature among m-PCMs on the solidification process has also been studied. A new boundary condition was defined to determine the combined effect of the Re and Ste numbers on the discharging process. The modelling results show that for a given input power, the Ste (or Re) number has a significant impact on the discharging process; however, the period value of inlet velocity has almost no impact on it. Besides, the zigzag plate with m-PCMs has a good impact on the temperature shock as “filter action” in the discharging process.

Beschreibung: Understanding runoff generation and dynamics is the basis for water resource management, while water isotopic ratios are a potential tool for studying the mechanism on a large scale. In this paper, spatial variations of δ18O and δD of river water and their sources within a large region of the Tarim River were investigated. The results showed obvious spatial variations of both water isotope values along the river flow direction, and significant seasonal variation occurred within the river water isotopes. This indicated that different proportions of rain and melt water entering river water should lead to spatial variation, and for mid-stream and downstream regions, the transformation relationship between surface water and groundwater should consider less input of melt water. Furthermore, we quantitatively determine the ratio of different water sources using the stable isotope mass balance method and other stable tracer elements. Results showed the contribution of ice-snowmelt water varied from 14.97% to 40.85%, that of rain varied from 9.04% to 54.80%, and that of groundwater varied from 15.34% to 58.85%, and they also showed that baseflow is a factor connecting melt water and groundwater, which meant the Hotan River and the Yarkand River are melt water–dependent rivers, and seasonal precipitation is the main water supply source of baseflow in the Aksu River and the Kaidu River.

Beschreibung: Rice growth monitoring is very important as rice is one of the staple crops of the world. Rice variables as quantitative indicators of rice growth are critical for farming management and yield estimation, and synthetic aperture radar (SAR) has great advantages for monitoring rice variables due to its all-weather observation capability. In this study, eight temporal RADARSAT-2 full-polarimetric SAR images were acquired during rice growth cycle and a modified water cloud model (MWCM) was proposed, in which the heterogeneity of the rice canopy in the horizontal direction and its phenological changes were considered when the double-bounce scattering between the rice canopy and the underlying surface was firstly considered as well. Then, three scattering components from an improved polarimetric decomposition were coupled with the MWCM, instead of the backscattering coefficients. Using a genetic algorithm, eight rice variables were estimated, such as the leaf area index (LAI), rice height (h), and the fresh and dry biomass of ears (Fe and De). The accuracy validation showed the MWCM was suitable for the estimation of rice variables during the whole growth season. The validation results showed that the MWCM could predict the temporal behaviors of the rice variables well during the growth cycle (R2 > 0.8). Compared with the original water cloud model (WCM), the relative errors of rice variables with the MWCM were much smaller, especially in the vegetation phase (approximately 15% smaller). Finally, it was discussed that the MWCM could be used, theoretically, for extensive applications since the empirical coefficients in the MWCM were determined in general cases, but more applications of the MWCM are necessary in future work.

Beschreibung: Remote Sensing, Vol. 10, Pages 534: The Consideration of Formal Errors in Spatiotemporal Filtering Using Principal Component Analysis for Regional GNSS Position Time Series Remote Sensing doi: 10.3390/rs10040534 Authors: Weiwei Li YunZhong Shen In the daily operation of regional GNSS (Global Navigation Satellite System) networks, the formal errors of all stations’ coordinate components are calculated. However, spatiotemporal filtering based on traditional Principal Component Analysis (PCA) for regional GNSS position time series does not take these formal errors into account. This paper developed a PCA-based approach to extract Common Mode Error (CME) from the position time series of a regional GNSS station network, where formal errors were applied to construct a weight factor. Because coordinate components with larger errors have smaller weight factors in extracting CME, the performance of our proposed approach was anticipated to be better than the traditional PCA approach. The position time series of 25 stations in the Yunnan Province, China, were analyzed using our approach, as well as the traditional PCA approach. The average errors of the residual time series after removing the CMEs with our approach were 1.30 mm, 1.72 mm, and 4.62 mm for North, East and Up components, and the reductions with respect to those of the original time series were 18.23%, 15.42%, and 18.25%, respectively. If CMEs were removed from the traditional PCA approach, the corresponding average errors were 1.34 mm, 1.81 mm, and 4.84 mm, with reductions of 15.84%, 10.86%, and 14.32%, respectively. Compared to the traditional PCA approach, the average errors of our approach were reduced by about 2.39%, 4.56%, and 3.93% in the North, East and Up components, respectively. Analysis of CME indicated that it mainly contained white and flicker noise. In the synthetic position time series with 500 repeated simulations, the CME extracted by our approach was closer to the true simulated values than those extracted by the traditional PCA approach, regardless of whether local effects were considered or not. Specifically, the mean root mean square (RMS) reduction of our approach, relative to PCA, ranged from 1.35% to 3.93%. Our simulations illustrated that the RMS reductions depended not only on the magnitude, but also the variation of the formal error series, which further highlights the necessity of considering formal errors in spatiotemporal filtering.

Beschreibung: Water, Vol. 10, Pages 468: Estimation of the Source Apportionment of Phosphorus and Its Responses to Future Climate Changes Using Multi-Model Applications Water doi: 10.3390/w10040468 Authors: Jian Sha Zhong-Liang Wang Rui Lu Yue Zhao Xue Li Yun-Tao Shang The eutrophication issue in the Yangtze Basin was considered, and the phosphorus loads from its tributary, the Modaoxi River, were estimated. The phosphorus flux and source apportionment of the Modaoxi River watershed were modeled and quantified, and their changes with respect to future projected climate scenarios were simulated with multiple model applications. The Regional Nutrient Management (ReNuMa) model based on Generalized Watershed Loading Functions (GWLF) was employed as a tool to model the hydrochemical processes of the watershed and thereby estimate the monthly streamflow and the phosphorus flux as well as its source apportionment. The Long Ashton Research Station Weather Generator (LARS-WG) was used to predict future daily weather data through the statistical downscaling of the general circulation model (GCM) outputs based on projected climate scenarios. The synthetic time series of daily precipitation and temperatures generated by LARS-WG were further used as input data for ReNuMa to estimate the responses of the watershed hydrochemical processes to future changed climate conditions. The results showed that both models could be successfully applied and that the future wetter and warmer climate trends would have generally positive impacts on the watershed phosphorus yields, with greater contributions coming from runoff. These results could provide valuable support for local water environmental management.

Beschreibung: Minerals, Vol. 8, Pages 102: Large-Scale Consumption and Zero-Waste Recycling Method of Red Mud in Steel Making Process Minerals doi: 10.3390/min8030102 Authors: Guoshan Ning Bo Zhang Chengjun Liu Shuai Li Yun Ye Maofa Jiang To release the environmental pressure from the massive discharge of bauxite residue (red mud), a novel recycling method of red mud in steel making process was investigated through high-temperature experiments and thermodynamic analysis. The results showed that after the reduction roasting of the carbon-bearing red mud pellets at 1100–1200 °C for 12–20 min, the metallic pellets were obtained with the metallization ratio of ≥88%. Then, the separation of slag and iron achieved from the metallic pellets at 1550 °C, after composition adjustment targeting the primary crystal region of the 12CaO·7Al2O3 phase. After iron removal and composition adjustment, the smelting-separation slag had good smelting performance and desulfurization capability, which meets the demand of sulfurization flux in steel making process. The pig iron quality meets the requirements of the high-quality raw material for steel making. In virtue of the huge scale and output of steel industry, the large-scale consumption and zero-waste recycling method of red mud was proposed, which comprised of the carbon-bearing red mud pellets roasting in the rotary hearth furnace and smelting separation in the electric arc furnace after composition adjustment.

Beschreibung: Sensors, Vol. 18, Pages 2271: Inversion of Rice Biophysical Parameters Using Simulated Compact Polarimetric SAR C-Band Data Sensors doi: 10.3390/s18072271 Authors: Xianyu Guo Kun Li Yun Shao Zhiyong Wang Hongyu Li Zhi Yang Long Liu Shuli Wang Timely and accurate estimation of rice parameters plays a significant role in rice monitoring and yield forecasting for ensuring food security. Compact-polarimetric (CP) synthetic aperture radar (SAR), a good compromise between the dual- and quad-polarized SARs, is an important part of the new generation of Earth observation systems. In this paper, the ability of CP SAR data to retrieve rice biophysical parameters was explored using a modified water cloud model. The results showed that S1 was superior to other CP variables in rice height inversion with a coefficient of determination (R2) of 0.92 and a root-mean-square error (RMSE) of 5.81 cm. RL was the most suitable for inverting the volumetric water content of the rice canopy, with an R2 of 0.95 and a RMSE of 0.31 kg/m3. The m-χ decomposition produced the highest accuracies for the ear biomass: R2 was 0.89 and RMSE was 0.17 kg/m2. The highest accuracy of leaf area index (LAI) retrieval was obtained for RH (right circular transmit and horizontal linear receive) with an R2 of 0.79 and a RMSE of 0.33. This study illustrated the capability of CP SAR data with respect to retrieval of rice biophysical parameters, especially for height, volumetric water content of the rice canopy, and ear biomass, and this mode may offer the best option for rice-monitoring applications because of swath coverage.

Beschreibung: Greater contradiction and conflict among urban green space, the development of social economy and the environment have occurred in Beijing. However, few studies have been conducted that consider the three subsystems as a whole. In this study, we defined sustainable development of green space (SDGS) as the coordinated development of the urban green system, social economy, and environment. Based on the datasets from 2000 to 2015, we forecast the SDGS in Beijing under multiple scenarios based on real-world policies using a system dynamics model. We found that the historical SDGS value increased to its highest level in 2012, but declined slightly by 2015. Second, the forecasted SDGS values declined over time in all scenarios, but the decline was greater in scenarios placing a high priority on economic development. In these scenarios, the performance of the indices only improved in certain subsystems. The simulation shows the implementation of the four policies proposed by the government failed to improve the overall level of SDGS in Beijing. This study could provide support for decision-making designed to improve the overall condition of urban green space in Beijing through integrated forecast and scenario simulation.

Beschreibung: Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection.