This paper investigates the volatility spillover effects and the dynamic relationships among WTI crude oil, gold and the Chinese stock markets of new energy vehicle, environmental protection, new ...energy, coal & consumable fuels, high and new technology, by adopting the method of Diebold and Yilmaz (2012, 2014) based on TVP-VAR model. The results indicate that there exists a high interdependence among all analyzed assets, and the total volatility spillover has a sharp increase under the major crisis events. On average, WTI crude oil and gold are the net receivers of the systemic shocks, while all of the analyzed stock markets are the net transmitters of the systemic shocks. Besides, the Granger causality test shows that the volatility of each asset can Granger cause the total connectedness index. Finally, we also calculate optimal hedge ratios, portfolio weights and the corresponding hedging effectiveness based on DCC-GARCH-t copula model. The empirical results show WTI crude oil and gold are cheap hedging tools. When investing a small part in WTI crude oil and a large part in the analyzed stock markets, high hedging effectiveness could be achieved.
•This paper examines time-varying spillovers among crude oil, gold and new energy vehicle.•The total volatility spillover has a sharp increase under the major crisis events.•New energy vehicle, new energy, new technology enterprises are the net transmitter of systematic shocks.•WTI crude oil futures, coal & consumable fuels and gold futures are the net receiver of systematic shocks.•WTI crude oil and gold futures are cheap hedging tools and gold is also a strong hedge.
•Headward erosion during the breaching process of landslide dams is developed.•A dam break model with six modules based on failure mechanism is proposed.•An empirical model to estimate the breach ...depth of landslide dams is given.•The diversion channel is an effective measure to reduce hazards due to dam break.
Landslide dams often fail shortly after the formation, resulting in huge risks to the downstream residents and properties. Fast and accurate forecasting of the breaching process and discharge hydrograph is important for a decision making to mitigate the damages. Morphological data indicate that the longitudinal length of most landslide dams is much larger than their transverse length. Additionally, headward erosion is more intense in landslide dams than manmade dams during the overtopping failure process. However, most existing models neglect this phenomenon. The objective of this study is to build up a dam-break model considering the headward erosion process, assuming that the change rate of downstream slope-angle is consistent with the rate of breach vertical erosion. And a dam-break numerical model to simulate the overtopping failure process of landslide dams considering the headward erosion was developed based on the theories of hydraulics, hydrology, soil mechanics, sediment dynamics, and etc. Nevertheless, the breach final bottom elevation, which can only be measured after the dam failure, is directly applied in currently available dam break models. To overcome this problem and for the prediction purpose of a newly formed landslide dam, we proposed an empirical model to estimate the breach final bottom elevations of high, medium and low erodibility landslide dams based on the statistical analysis of worldwide landslide dam failure cases collected recently. To verify the effectiveness of proposed dam-break numerical model, the ‘11.03′ Baige landslide dam which locates at the border of Tibet Autonomous Region and Sichuan province was selected as a case study. Results of this study show that the relative errors in the simulated peak discharge, time to the peak, and the total flood volume are 1.59%, 3.50% and 0.53%, respectively, which meet the accuracy requirements of hydrological forecasting. The relative error in the prediction of breach final bottom elevation is 4.28%, which indicates that the accuracy of the simulation is satisfactory. Finally, a sensitivity analysis indicates that the downstream slope affects the prediction of the breach and flood hydrograph significantly, and the excavation of diversion channel is an effective measure to reduce the peak discharge of dam overtopping failure.
is widely used as the model species in toxicity and risk assessment. For the first time, a global classification model was proposed in this paper for a two-class problem (Class - 1 with log1/IBC
≤ ...4.2 and Class + 1 with log1/IBC
> 4.2, the unit of IBC
: mol/L) by utilizing a large data set of 601 toxicity log1/IBC
of organic compounds to
. Dragon software was used to calculate 4885 molecular descriptors for each compound. Stepwise multiple linear regression (MLR) analysis was used to select the descriptor subset for the models. The ten molecular descriptors used in the classification model reflect the structural information on the Michael-type addition of nucleophiles, molecular branching, molecular size, polarizability, hydrophobic, and so on. Furthermore, these descriptors were interpreted from the point of view of toxicity mechanisms. The optimal support vector machine (SVM) model (
= 253.8 and
= 0.009) was obtained with the genetic algorithm. The SVM classification model produced a prediction accuracy of 89.1% for the training set (451 log1/IBC
), of 80.0% for the test set (150 log1/IBC
), and of 86.9% for the total data set (601 log1/IBC
), which are higher than that (80.5%, 76%, and 79.4%, respectively) from the binary logistic regression (BLR) model. The global SVM classification model is successful, although it deals with a large data set in relation to the toxicity of organics to
.
•Height of 99.41% of CloudSat surface snowfall events are >1km above the surface, whereas 76.41% of corresponding NOAA/NSSL ground radar (Q3) observations are low below 1km to the near ground ...surface.•69.40% of snowfall events detected by 69.40 were classified as certain snow by CPR.•CloudSat shows less certain snow precipitation than Q3 by 26.13% with a low CC (0.41) with Q3 and a high RMSE (0.6mm/h).•CloudSat underestimates (overestimates) certain snowfall than Q3 when the bin height of detected snowfall events below (above) 3km.
The latest global snowfall product derived from the CloudSat Cloud Profiling Radar (2C-SNOW-PROFILE) is compared with NOAA/National Severe Storms Laboratory’s Multi-Radar Multi-Sensor (MRMS/Q3) system precipitation products from 2009 through 2010. The results show that: (1) Compared to Q3, CloudSat tends to observe more extremely light snowfall events (<0.2mm/h) and snowfall rate (SR) between 0.6 to 1mm/h, and detects less snowfall events with SR between 0.2–0.5mm/h. (2) CloudSat identifies 69.40% of snowfall events detected by Q3 as certain snow and 10% as certain mixed. When possible snow, possible mixed, and certain mixed precipitation categories are assumed to be snowfall events, CloudSat has a high snowfall POD (86.10%). (3) CloudSat shows less certain snow precipitation than Q3 by 26.13% with a low correlation coefficient (0.41) with Q3 and a high RMSE (0.6mm/h). (4) With Q3 as reference, CloudSat underestimates (overestimates) certain snowfall when the bin height of detected snowfall events are below (above) 3km, and generally overestimates light snowfall (<1mm/h) by 7.53%, and underestimates moderate snowfall (1–2.5mm/h) by 42.33% and heavy snowfall (⩾2.5mm/h) by 68.73%. (5) The bin heights of most (99.41%) CloudSat surface snowfall events are >1km high above the surface, whereas 76.41% of corresponding Q3 observations are low below 1km to the near ground surface. This analysis will provide helpful reference for CloudSat snowfall estimation algorithm developers and the Global Precipitation Measurement (GPM) snowfall product developers to understand and quantify the strengths and weaknesses of remote sensing techniques and precipitation estimation products.
The majority of fruits and vegetables are perishable, thus finding sustainable postharvest treatments to regulate the quality of fresh produce is imperative. Recent research has demonstrated that the ...exogenous application of hydrogen (H2)-associated treatments such as H2 gas or hydrogen-rich water (HRW), hydrogen sulfide (H2S), and hydrogen peroxide (H2O2) at optimal concentrations can significantly maintain the quality of postharvest fruits and vegetables. The understanding of mode of action of such treatments for quality maintenance and shelf-life extension of harvested fruits and vegetables has undergone substantial development in recent years. This paper addressed recent trends in functionalities of H2-associated treatments, summarizes the modulations led by possible mechanism of action, lab-scale production strategies, quality-regulating aspects at both physiological and transcriptomics levels, and limitations in H2-associated treatments for maintaining postharvest quality of fresh and fresh-cut fruits and vegetables, and suggests future research directions aimed at developing sustainable H2-associated postharvest treatment. The key findings of this review mainly concluded that H2-associated treatments are proven to be promising approaches for maintaining the quality of fresh and fresh-cut fruits and vegetables, notably by delaying senescence, reducing softening, alleviating chilling injury, lowering the browning, and limiting microbial proliferation by modulating gas respiratory, antioxidant, and peroxiredoxin/thioredoxin systems; phenylpropanoid, GABA-shunt, and AsA biosynthesis pathways; mitochondrial energy, cell wall, color, proline, and lipid metabolisms, and ROS and RNS homeostasis. Future research direction emphasizes the application of hydrogen nanobubble water (HNW), and H2-associated treatments in combination to regulate overall quality of fresh and fresh-cut fruits and vegetables.
The traditional passive azimuth estimation algorithm using two hydrophones, such as cross-correlation time-delay estimation and cross-spectral phase estimation, requires a high signal-to-noise ratio ...(SNR) to ensure the clarity of the estimated target trajectory. This paper proposes an algorithm to apply the frequency diversity technique to passive azimuth estimation. The algorithm also uses two hydrophones but can obtain clear trajectories at a lower SNR. Firstly, the initial phase of the signal at different frequencies is removed by calculating the cross-spectral density matrix. Then, phase information between frequencies is used for beamforming. In this way, the frequency dimension information is used to improve the signal processing gain. This paper theoretically analyzes the resolution and processing gain of the algorithm. The simulation results show that the proposed algorithm can estimate the target azimuth robustly under the conditions of a single target (SNR = -16 dB) and multiple targets (SNR = -10 dB), while the cross-correlation algorithm cannot. Finally, the algorithm is tested by the swell96 data and the South Sea experimental data. When dealing with rich frequency signals, the performance of the algorithm using two hydrophones is even better than that of the conventional broadband beamforming of the 64-element array. This further validates the effectiveness and advantages of the algorithm.
High performance expanded graphite (EG)–multiwalled carbon nanotube (MWCNT)/cyanate ester (CE) composites with very high dielectric constant, low dielectric loss and low percolation threshold were ...developed. In order to understand the electric and dielectric behavior of EG–MWCNT/CE composites, EG/CE and MWCNT/CE binary composites were also prepared for comparison. Results show that the ternary composites have greatly different electric and dielectric properties from the binary composites. The percolation threshold of the EG–MWCNT/CE composite is much lower than that of either the EG/CE or MWCNT/CE composite. With the same content of conductive fillers, the EG–MWCNT/CE composite shows a much higher dielectric constant than EG/CE and MWCNT/CE composites. In addition, to obtain the same dielectric constant, the dielectric loss of the EG–MWCNT/CE composite is lower than that of either binary composite. The difference is attributed to the synergistic effect between EG and MWCNT. The addition of EG not only improves the dispersion of MWCNTs in the resin matrix, but also helps to form conductive networks. An equivalent circuit model is proposed.
•Ethylene regulation at preharvest altered fruit carbohydrate content during storage.•Harvista retarded fruit carbohydrate metabolism during storage at molecular level.•Harvista reduced the fruit ...dropping rate and maintained apple fruit storage quality.•Harvista is an useful and convenient tool to delay fruit ripening for best quality.
The main purpose of this study was to investigate the effects of preharvest regulation of ethylene on apple fruit carbohydrate metabolism and quality at harvest and during storage. The positive regulation of ethylene was achieved by Ethephon, and the negative regulation was by Harvista, a kind of sprayable 1-methylcyclopropylene (1-MCP). ‘Starkrimson’ apple were treated with Harvista or Ethephon 7 d before harvest, respectively, and then stored at 0 °C for 180 d. The contents of starch, sucrose, glucose, fructose, and related enzymes activities and gene expression levels of sucrose phosphate synthase (SPS), sucrose synthase (SUSY), acid invertase (AINV), neutral invertase (NINV), cell wall invertase (CWINV) and amylase (AMY) were determined. The results showed that Harvista inhibited the starch degradation, retarded the increase of soluble sugar, reducing sugar, sucrose, glucose and fructose contents before 120 d of fruit storage, while no obvious difference was observed in these sugar content after 120 d of storage among three treatments. The enzyme activities of SPS, AINV, CWINV and AMY were also inhibited by Harvista at the early period of storage, and the expression levels of MdSPS, MdAINV, MdCWINV and MdAMY were positively correlated with their enzyme activities. In addition, Harvista reduced the fruit dropping rate at harvest and maintained the fruit firmness, while Ethephon showed the opposite effect. These results indicated that the preharvest regulation of ethylene effectively altered the carbohydrate metabolism and the quality of ‘Starkrimson’ apple fruit, and Harvista may be a useful tool applied at preharvest to maintain fruit quality at harvest and during storage.
The effects of hot air (HA) pretreatment on quality, phenolic accumulation and antioxidant activity of fresh-cut pitaya fruit were investigated. It was found that 42 °C HA pretreatment for 3 h ...effectively alleviated the browning of fresh-cut pitaya fruit stored at both 4 °C for 14 d and 20 °C for 48 h. To better understand the physiological mechanisms of HA on browning alleviation, higher storage temperature at 20 °C was used to accelerate and amplify the wounding responses. The results demonstrated that HA pretreatment delayed the wound induced biosynthesis of phenolic compounds of fresh-cut pitaya fruit during earlier storage period but enhanced their contents and maintained higher antioxidant activity during the later stage of storage. It retarded but enhanced the activation of key enzymes (PAL, 4CL and C4H) and their relative gene expressions involved in the phenylpropanoid pathway. Moreover, HA pretreatment suppressed the activities of enzymes associated with oxidative browning of phenolics (PPO and POD), activated ascorbate-glutathione (AsA-GSH) cycle and inhibited the wound induced proliferation of ROS production which could cause oxidative damage of fresh-cut pitaya fruit. These findings suggested that pretreatment with HA could be an efficient and feasible approach for the browning alleviation and quality retention of fresh-cut pitaya fruit, and the phenylpropanoid metabolism and AsA-GSH cycle played crucial roles in this process.
•Hot air (HA) pretreatment alleviated browning of fresh-cut pitaya fruit.•HA pretreatment delayed but enhanced the wound-induced phenolic accumulation.•HA pretreatment reduced PPO and POD activities.•HA pretreatment enhanced antioxidant system and reduced ROS level.
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