In this study, farmland and mining ecotypes of Solanum photeinocarpum (a potential cadmium (Cd) hyperaccumulator plant) were reciprocally hybridized each other, and the Cd accumulation characteristics of the F1 hybrids were studied. In pot experiments, higher biomasses and Cd extraction abilities were found for two S. photeinocarpum F1 hybrids than for the parents, but the Cd contents in various organs were lower in the hybrids than the parents. However, the differences between the Cd contents in the two hybrids were not significant. The antioxidant enzyme (superoxide dismutase and peroxidase) activities were higher for the S. photeinocarpum F1 hybrids than the parents. Less DNA methylation was found in the hybrids than the parents because more demethylation occurred in the hybrids than the parents. The biomass, Cd content, and Cd extraction ability effects in field experiments were similar to the effects in the pot experiments. It was concluded that reciprocally hybridizing different S. photeinocarpum ecotypes improved the ability of S. photeinocarpum to be used to phytoremediate contaminated land.
Channa argus, a type of snakehead fish native to China, is a popular food fish in certain Asian countries but is a known destructive invasive species in the US. In this study, the two collagens, i.e. acid-soluble collagen (ASC) and pepsin-solubilized collagen (PSC), were obtained from C. argus skin. The yield of ASC was 28.0% and that of PSC was 16.8% on the dry bases. The collagens were identified as the collagen of type I by SDS–PAGE patterns. The Tds were approximately 27.0?°C. Similar ultraviolet spectra of both collagens were observed. Fourier Transform infrared spectra indicated PSC structure had a little change due to the loss of terminal domains by pepsin digestion. The results of XRD proved that the two collagens retained their helical structures. The results suggest that the collagens isolated from C. argus can potentially be alternative sources of vertebrate collagens for use in the food and other industries. 相似文献
Objective: Intersection movement assist (IMA) has been recognized as one of the prominent countermeasures to reduce angle crashes at intersections, which constitute 22% of total crashes in the United States. Utilizing vehicle-based sensors, vehicle-to-vehicle (V2V), and vehicle-to-infrastructure (V2I) communications, IMA offers extended vision to provide early warning for an imminent crash. However, most of IMA-related research implements their methods and strategies only in simulations, test tracks, or driving simulator studies that have quite a few assumptions and limitations and hence the effectiveness evaluations reported may not be transferable or comparable.
Methods: This study seeks to develop a generalized evaluation scheme that can be used not only to assess the effectiveness of IMA on improving traffic safety at intersections but to facilitate comparisons across similar studies. The proposed evaluation scheme utilizes the concepts of traffic conflict in terms of time-to-collision (TTC) as a crash surrogate. This approach avoids the issue of having insufficient crash frequency data for system evaluation. To measure the effectiveness of IMA on reducing traffic conflicts, a relative risk is calculated for comparing the risk of with/without using the IMA. As a proof-of-concept study, this study applied the proposed evaluation scheme and reported the effectiveness of IMA on improving traffic safety in a field operation test (FOT). Seven test scenarios were conducted at 4 intersections, and a total of 40 participants were recruited to use the IMA for 6 months.
Results: It was estimated that IMA users have 26% fewer conflicts with TTC less than 5 s and have 15% fewer conflicts with TTC less than 4 s. However, the results vary across different sites and different definitions of conflicts in terms of TTC.
Conclusions: Overall, IMA is promising to effectively reduce angle crashes related to sight obstruction and has potential to reduce not only crash frequency but crash severity. 相似文献
Soybean meal (SBM) is a product generated from the manufacture of soybean oil and has the potential for use as a source of fermentable sugars for ethanol production or as a protein source for animal feeds. Knowing the levels of nitrogen available from ammonium is a necessary element of the ethanolic fermentation process while identifying the levels of essential amino acids such as lysine is important in determining usage as a feed source. As such the purpose of this study was to quantify total nitrogen and ammonium in the liquid fraction of hydrolyzed SBM and to evaluate total and bioavailable lysine in the solid fraction of the hydrolyzed SBM. The effects of acid concentration, cellulase and β-glucosidase on total and ammonium nitrogen were studied with analysis indicating that higher acid concentrations increased nitrogen compounds with ammonium concentrations ranging from 0.20 to 1.24 g L?1 while enzymatic treatments did not significantly increase nitrogen levels. Total and bioavailable lysine was quantified by use of an auxotrophic gfpmut3 E.coli whole-cell bioassay organism incapable of lysine biosynthesis. Acid and enzymatic treatments were applied with lysine bioavailability increasing from a base of 82% for untreated SBM to up to 97%. Our results demonstrated that SBM has the potential to serve in ethanolic fermentation and as an optimal source essential amino acid lysine. 相似文献
Unlike the European Union emission trade system (EU ETS), China’s pilot ETSs implemented diversified policy designs instead of using a uniform framework. Variance ratio test is used to evaluate the Efficient Market Hypothesis (EMH) in China’s carbon trading markets. The results of two versions of variance ratio tests indicate that the carbon trading market in Hubei is considered weak form efficient, and the socialist market economy does not necessarily lead to market inefficiency in carbon trading markets. Thin trading activities generate market frictions and bias the Efficient Market Hypothesis (EMH) tests. 相似文献
Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%. 相似文献