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The polarization crossfire (PCF) suite carried onboard the Chinese GaoFen-5B satellite is composed of a Particulate Observing Scanning Polarimeter (POSP) and a Directional Polarimetric Camera (DPC), which can provide multi-angle, multi-spectral, and polarization data. In this paper, the influence of polarization and the directionality of reflectance in open oceans on the inversion of chlorophyll a (Chla) concentrations are investigated, from 410 nm to 670 nm. First, we exploit a vector radiative transfer model to simulate the absolute and relative magnitudes of the water-leaving radiance signal (I) and the parallel polarization radiance (PPR) to the top-of-atmosphere (TOA) radiation field. The simulation results show that the PPR can enhance the relative contribution of the water-leaving signal, especially in sunglint observation geometry. The water-leaving signal for PPR exhibits significant directional and spectral variations relative to the observation geometries, and the maximum value of the water-leaving signal for PPR occurs in the backscattering direction. In addition, the sensitivity of the PPR to the Chla concentration is sufficient. The synthetic datasets are utilized to develop retrieval algorithms for the Chla concentrations based on the back-propagation neural network (BPNN). The inversion results show that the PCF strategy improves the accuracy of Chla retrieval, with an RMSE of 0.014 and an RRMSE of 6.57%. Thus, it is an effective method for retrieving the Chla concentration in open oceans, by utilizing both the directionality and polarization of the reflectance. [ABSTRACT FROM AUTHOR]

Beer is susceptible to mycotoxin contamination originating from infected grains. It could be that mycotoxins are not completely removed during the brewing process and remain in the final product. Nevertheless, there have been no surveys of exposure to mycotoxin for Chinese inhabitants through beer consumption. This study aimed to investigate the presence of eight mycotoxins in 158 beer samples purchased in Shanghai, the largest megacity in China. The multiple mycotoxins determination was carried out using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Our findings revealed that 48.1% (76/158) of the beer samples were contaminated with Fusarium toxins. Deoxynivalenol-3-glucoside (D3G) and zearalenone (ZEN) were detected in 34.81% and 16.46% of the total samples, respectively. The significant differences between D3G/ZEN contamination and various beer types were performed. Furthermore, this study performed a health risk assessment for Shanghai residents based on data for Fusarium toxins and ochratoxin A (OTA) present in beer for the first time. The results revealed that the 95th percentile dietary exposures of Shanghai residents did not pose any chronic or acute health risks, either individually or in combination. Dietary exposures to Fusarium toxins revealed different risk levels among residents. The cumulative health risk for women is higher than that for men at the same beer consumption. In addition, the acute risk of DONs exposure for adults deserves concern. The insights obtained from this study may be of assistance for beer manufacturers and governmental regulators to further develop beer monitoring and guarantee public health. [ABSTRACT FROM AUTHOR]

To achieve the harmonious development of economic growth and the environment, nations must pay more attention to wastewater treatment and boost efficiency using green technology. This study applies the Malmquist-DEA model to assess the efficiency of green technology innovation in 19 Chinese wastewater treatment companies between 2017 and 2020. In addition, focus is placed on the core wastewater treatment technology of the companies with excellent performance, indicating how wastewater treatment companies may improve their green technology. The results of the study indicate that, first, the overall effectiveness of green technology innovation in companies follows a rising and then decreasing trend. In 2020, wastewater treatment companies' green technology innovation efficiency was around 17.4 percent lower than in 2017. Improving technical progress is the key to boosting the total factor productivity of wastewater treatment companies. Second, based on the Tobit regression, the shareholding ratio of companies has a positive influence on the technical efficiency of companies. Therefore, China should increase innovation capacity and productivity, adopt current sewage treatment technology from overseas, and thus gradually achieve clean sewage utilization and ecological environment management. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) is a multisystem and complex metabolic disorder which is associated with insulin resistance and impairments of pancreatic β-cells. Previous studies have shown that icariside II (ICS II), one of the main active ingredients of Herba Epimedii, exerts potent anti-inflammatory and anti-oxidative properties. In this study, we investigated whether ICS II exerted anti-T2DM profile and further explored its possible underlying mechanism both in vivo and in vitro. db/db mice were administered ICS II (10, 20, 40 mg·kg−1) for 7 weeks. We found that ICS II dose-dependently attenuated hyperglycemia and dyslipidemia, as well as inhibited hepatic steatosis and islet architecture damage in db/db mice. Moreover, ICS II not only dramatically reduced inflammatory cytokines and oxidative stress, but also up-regulated PPARα/γ protein expressions, phosphorylation of Akt, GSK3β and IR, meanwhile, down-regulated phosphorylation of NF-κB(p65) and IRS1 in db/db mice. In palmitic acid (PA)-treated HepG2 or MIN6 cells, ICS II (5−20 μM) concentration-dependently promoted the cell viability via mediating PPARα/γ/NF-κB signaling pathway. PPARα/γ knockout by CRISPR-Cas9 system partly abolished the protective effects of ICS II on HepG2 or MIN6 cells following PA insults. These findings reveal that ICS II effectively confer anti-T2DM property by targeting PPARα/γ through mediation of ROS/NF-κB/IRS1 signaling pathway. [ABSTRACT FROM AUTHOR]

Effect of ICS II on SIRT3-KO Mice To further verify if loss of functional SIRT3 offsets ICS II preconditioning-induced cardioprotection in MI, WT and SIRT3-KO mice were treated with or without ICS II for 7 days prior to MI. ICS II Mitigated MI-Induced Myocardial Injury in Mice The left anterior descending coronary artery ligation-induced MI mice model was used to determine the effect of ICS II on MI-induced myocardial injury. Icariside II, a Naturally Occurring SIRT3 Agonist, Protects against Myocardial Infarction through the AMPK/PGC-1 /Apoptosis Signaling Pathway ICS II Inhibited Myocardial Apoptosis in Mice after MI We next investigated the role of apoptosis in the inhibitory effect of ICS II on MI. [Extracted from the article]

Attitude error models play an important role in analyzing the characteristics of navigation error propagation for the design and operation of strapdown inertial navigation systems (SINS). However, the majority of existing attitude error models focus on misalignment, rather than Euler angle errors. Misalignment cannot directly describe attitude error propagation, which is an indirect measurement. To solve the problem, a general Euler angle error model of SINS is proposed. Based on Euler angle error propagation analysis, relative Euler angle errors, and convected Euler angle errors are introduced to compose the general Euler angle error model. Simulation experiments are carried out to verify the proposed model. [ABSTRACT FROM AUTHOR]

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers' willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against the day-ahead IDR bids, and the conditional value-at-risk (CVaR) theory is introduced to enhance the robustness of the scheduling model under different prediction accuracies. The case study demonstrates that the proposed method can reduce the operating cost of the community under the premise of fully considering users' willingness, and can complete the IDR request initiated by the power grid operator or the dispatching department. [ABSTRACT FROM AUTHOR]

Because of the high penetration of renewable energies and the installation of new control devices, modern distribution networks are faced with voltage regulation challenges. Recently, the rapid development of artificial intelligence technology has introduced new solutions for optimal control problems with high dimensions and dynamics. In this paper, a deep reinforcement learning method is proposed to solve the two-timescale optimal voltage control problem. All control variables are assigned to different agents, and discrete variables are solved by a deep Q network (DQN) agent while the continuous variables are solved by a deep deterministic policy gradient (DDPG) agent. All agents are trained simultaneously with specially designed reward aiming at minimizing long-term average voltage deviation. Case study is executed on a modified IEEE-123 bus system, and the results demonstrate that the proposed algorithm has similar or even better performance than the model-based optimal control scheme and has high computational efficiency and competitive potential for online application. [ABSTRACT FROM AUTHOR]