Nitrate is one of the most common chemical contaminants of groundwater, and it is an important unqualified factor of rural groundwater in Yantai. In order to assess the risk of exposure to drinking ...water nitrate for adults and juveniles, in recent years, we monitored the nitrate concentrations in rural drinking water,a model was also used to assess the human health risk of nitrate pollution in groundwater.
From the year 2015 to 2018, the drinking water in rural areas of Yantai was tested according to the "Sanitary Standard for Drinking Water" (GB5749-2006). The principal component analysis was used to analyze the relationship between groundwater chemicals and nitrate. The model was used to assess human health risks of groundwater nitrate through the drinking water and skin contact.
A total of 2348 samples were tested during the year 2015-2018.Nitrate and total dissolved solids, total hardness, chloride are all relevant, the above indicators may come from the same source of pollution; The median nitrate content (C
) was 17.8 mg / L; the risk of exposure in each group was ranked as: Juveniles > Adult female > Adult male;the median health risk (HQ
) for minors and adults exceed 1.
The concentrations of nitrate is stable and does not change over time. The high concentration of nitrate in rural areas of Yantai may be the result of the interaction of fertilizers and geological factors. The risk of exposure to nitrate in juveniles and adults is above the limit, so it is necessary to be on the alert for the high levels of nitrate.
Massive smart water conservancy object (WCO) need to be connected for real-time monitoring and control, which produces massive data. Unfortunately, heterogeneous data structures and semantics lead to ...low interoperability between WCO and management systems. To address this challenge, we propose a novel interoperability structure for a smart water conservancy system based on the Internet of Things (IoT), and the key design includes a smart WCO terminal, interoperability network, special interoperability protocol, WCO information model, and cloud platform. Universal terminal and network are the base of interoperability hardware, and special interoperability protocol and information model for interconnection of WCO are designed for smart water conservancy management system. WCO can be connected to a water conservancy Big Data processing cloud platform for interoperability applications. The application results demonstrate that our proposed WCO’s interoperability structure has obvious advantages than the general IoT at WCO interoperability. The interoperability protocol is reliable, the information model can ease interoperability and security, and the semantic dictionary is very rich and covers all semantic services of WCO.
Due to the characteristics of strong suddenness, high harmfulness, and frequent occurrence of mountain flood disasters in small watersheds, the accuracy and reliability of mountain flood forecasting ...are insufficient in small watersheds. This paper study key theories and technologies, that is the uncertainty forecasting model based on hydrologic physical mechanism. We design the Bayesian Deep Learning (DL) forecasting models, it is suitable for the transfer of spatiotemporal factors caused by mountain floods to disaster probability. The models include Bayesian Linear and Bayesian Long Short-Term Memory (LSTM) model, we hope to achieve an acceptable balance between reliability (uncertainty confidence coverage) and accuracy (confidence interval width). Meanwhile, we extract effective information from multi-source and multi-dimensional hazard factors' big data. The experiment shows the differences between Bayesian DL models, the models have long-term probability forecasting ability at both, but Bayesian LSTM is superior to Bayesian Linear in terms of reliability and accuracy.
Due to the many disaster-causing factors of mountain torrents, rapid changes in time and space, and rapid disasters, the traditional hydrological models and general data-driven mountainous flood ...forecasting models in small watershed areas have low accuracy and timeliness. Therefore, this paper proposed the time series Recurrent Neural Networks (RNN) and data processing for small mountain flood level forecasting, it includes base RNN, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) model. We use the Tiaoxi catchment's mountain flood data including hydrology, meteorology, geography and human activities at Zhejiang province of China. We construct multi-dimensional time series data processing and the model test system, and develop multi-dimensional disaster factor data on an hourly scale to suit the training and prediction of Deep Learning (DL)'s structure. The experiment shows that time series base RNN, LSTM and GRU models can be considered as the efficient hydrology modeling approach. The LSTM model demonstrated the best accuracy and real-time in the study area.
Water conservancy equipment (WCE) has a large amount of information, structural heterogeneity and complex relationship leads to the difficulty of semantic interoperability in smart water conservancy. ...To overcome this issue, we propose the WCE information interaction dimension theory, modeling process and instancing method. First, we analyze the smart water conservancy ontology and information factor, and propose semantic information interaction dimension structure of water conservancy Ontology. Second, we construct the network information model structure of water conservancy, through the relationship degree, a tree model which can realize semantic expression and interoperability is formed through the dimensionality reduction of the model. Third, the component attribute set hierarchical relationship architecture water conservancy information model is established, which use XML language to describe this model. Moreover, the three types of instancing methods are proposed. Through OPC unified architecture (OPC UA) technology, water conservancy information model can implement semantic interoperability. The experimental show that the proposed method of semantic information modeling and semantic interoperability of WCE is feasible, and obvious advantages of complete semantic interoperability than in the model architecture, semantic structure and technical implementation.
Morphing wing aircraft have generated increasing interest in recent years owing to their ability to alter the shape and configuration of the wings to retain optimum flight performance under different ...flight conditions. However, while theoretical approaches have greatly advanced our understanding of the nonlinear vibrational characteristics of morphing wings during the morphing process, little effort has been made to verify the results of theoretical studies based on corresponding experimental results. The present work addresses this issue by first investigating the nonlinear dynamic behaviors of Z-shaped morphing wings during the morphing process in subsonic flow based on thin airfoil theory under ideal incompressible fluid conditions. First, the steady aerodynamic lift on the morphing wing is derived and the nonlinear partial differential equations governing the morphing wing motion are established. The influence of the folding angle on the nonlinear responses of the morphing wing is investigated via numerical simulations. Then, the aeroelastic characteristics of the morphing wing, including the flutter displacements of edge points on the outer plate of the wing, are investigated using the computational fluid dynamics module in ANSYS. Finally, the results of theoretical analysis are verified by experiments conducted with a corresponding Z-shaped morphing wing model.
Medicinal plant-derived vesicle-like nanoparticles can carry chemical components and exert intercellular activity due to the encapsulation of nanostructures. American ginseng is well known as a ...traditional herb and is commonly used in clinical decoctions. However, the nano-characteristics and chemical composition of American-ginseng-derived vesicle-like nanoparticles (AGVNs) in decoctions are unclear. In this study, the gradient centrifugation method was used to extract and isolate AGVNs. A metabolomic method based on high-resolution mass spectrometry was established to analyze small molecules loaded in AGVNs. Zebrafish and RAW264.7 cells were employed to investigate the anti-inflammatory effects of AGVNs. The results showed that the particle size of AGVNs was generally 243.6 nm, and the zeta potential was −14.5 mV. AGVNs were found to contain 26 ginsenosides (14 protopanaxadiols, 11 protopanaxatriols, and 1 oleanolic acid). Ginsenoside Rb1 and malonyl-ginsenoside Rb1 tended to be enriched in AGVNs. Moreover, AGVNs were found to exert anti-inflammatory effects by reducing macrophage migration in zebrafish and regulating inflammatory factor (NO, TNF-α, IL-6, IL-10) secretion in RAW 264.7 cells. The characterization and analysis of AGVNs provide references and data that support the development of nanoscale anti-inflammatory substances from medicinal plants.
To achieve high oxygen blocking structure of the ZrB
2
-MoSi
2
coating applied on carbon structural material, ZrB
2
-MoSi
2
coating was prepared by spark plasma sintering (SPS) method utilizing ZrB
2
...-MoSi
2
composite powders synthesized by self-propagating high-temperature synthesis (SHS) technique as raw materials. The oxygen blocking mechanism of the ZrB
2
-MoSi
2
coatings at 1973 K was investigated. Compared with commercial powders, the coatings prepared by SHS powders exhibited superior density and inferior oxidation activity, which significantly heightened the structural oxygen blocking ability of the coatings in the active oxidation stage, thus characterizing higher oxidation protection efficiency. The rise of MoSi
2
content facilitated the dispersion of transition metal oxide nanocrystals (5–20 nm) in the SiO
2
glass layer and conduced to the increasing viscosity, thus strengthening the inerting impact of the compound glass layer in the inert oxidation stage. Nevertheless, the ZrB
2
-40 vol%MoSi
2
coating sample prepared by SHS powders presented the lowest oxygen permeability of 0.3% and carbon loss rate of 0.29×10
−6
g·cm
−2
·s
−1
. Owing to the gradient oxygen partial pressure inside the coatings, the Si-depleted layer was developed under the compound glass layer, which brought about acute oxygen erosion.
Yindan xinnaotong, a compound preparation used in traditional Chinese medicine, is composed of eight herbs: Ginkgo biloba leaf (yinxingye), Salvia miltiorrhizae (danshen), Herba gynostemmatis ...(jiaogulan), Erigerontis herba (dengzhanxixin), Allii sativi bulbus (dasuan), Notoginseng radixe rhizoma (sanqi), Crataegi fructus (shanzha), and Borneolum (tianranbingpian). Yindan xinnaotong is primarily used to treat cardiovascular and cerebrovascular diseases. However, to date, no scientific methods have been established to assess the quality of Yindan xinnaotong. Therefore, a combinatorial method was developed based on chemical constituent identification and fingerprint analysis to assess the consistency of Yindan xinnaotong quality. In this study, ultra high performance liquid chromatography coupled with time‐of‐flight mass spectrometry was used to identify the chemical components of Yindan xinnaotong soft capsules. Approximately 74 components were detected, of which 70, including flavonoids, ginkgolide, phenolic acid, diterpenoid tanshinones, and ginsenoside, were tentatively identified. A fingerprint analysis was also conducted to evaluate the uniformity of the quality of Yindan xinnaotong soft capsules. Ten batches of Yindan xinnaotong soft capsules were analyzed. All of the resulting chromatograms were imported into the “Similarity Evaluation System for Chromatographic Fingerprints of TCM” (Chinese Pharmacopoeia Commission, version 2004A). The similarity scores of common peaks from these samples ranged from 0.903–1.000, indicating that samples from different batches were highly correlated.
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The hydrodynamic performance of three mixers (single shaft central mixer (SSC), single shaft off-centred mixer (SSO), dual shaft off-centred mixer (DSO), was investigated in the ...mixing of yield-pseudoplastic fluids (xanthan gum solutions) in the laminar regime. To explore and determine the efficiency of three mixers, both numerical and experimental approaches were adopted. The fluid rheology was described by the Herschel–Bulkley rheological model. Computational fluid dynamics was employed to simulate the apparent viscosity distribution, mixing time, and the flow pattern inside the stirred tank. The developed model was validated through experimentally measured torque. The influence mechanism of the rotational speed and fluid rheology on the cavern evolution was explored deeply. The performances of three mixers in this work were compared at the constant power input and fluid rheology with respect to the flow pattern, mixing time, and mixing efficiency. The results verify that the faster the rotating speed, the greater influence of the fluid rheology on the cavern evolution, and the more uniform apparent viscosity distribution. Moreover, the mixing time decreases continuously as the increasing power consumption per unit volume, and the dimensionless mixing time of DSO mixer was nearly 42.8% and 6.1% shorter than that of SSC and SCO mixer at the same Reynolds number, respectively. According to the mixing efficiency criteria, these data also revealed that DSO was more efficient than SSC and SSO.
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