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Recent studies have shown that lotus (Nelumbo nucifera) leaf has various pharmacological effects. However, there have been no scientific investigations into these leaves as a fermented crude liquid. This study compared the in vitro antioxidant capacity of lotus leaf‐fermented broth (LLFB) with that of 57° Brix sugar broth (SB) as a control over a period of 6 months based on 1,1‐diphenyl‐2‐picrylhydrazyl radical scavenging activity, ferric ion reducing power, superoxide dismutase‐like activity, tyrosinase inhibition and nitrite scavenging activity. The dominant species during fermentation process were Leuconostoc lactis and Saccharomyces cerevisiae for LLFB. A total of thirty‐six metabolites such as alkaloids, fatty acids, organic acids, phenolics, sugar and sugar derivatives, ethyl esters and monoterpenoids differed between SB and LLFB using gas chromatography–mass spectrometry. Meanwhile, nine volatile compounds in LLFB contributed pleasant, slightly sweetish and fruity odour of condiment and sensory evaluation score of 4.06 ± 1.52 in the proportion of 1:9 LLFB/water.  相似文献   
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Many e-commerce companies collect users’ personal data for marketing purposes despite privacy concerns. Information-collecting companies often offer a monetary reward to users to alleviate privacy concerns and ease the collection of personal information. This study focused on the negative effects of monetary rewards on both information privacy concerns (IPC) and information disclosure. A survey approach was used to collect data and 370 final responses were analysed using a two-way analysis of variance and a binomial logistic regression model. The results show that monetary rewards increase IPC when an information-collecting company requires sensitive information. Additional results indicate that building trust is a more effective way of collecting personal data. This study identifies how organisations can best execute information-collection activities and contributes additional insights for academia and practitioners.  相似文献   
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The high cost and potential toxicity of biodegradable polymers like poly(lactic‐co‐glycolic)acid (PLGA) has increased the interest in natural and modified biopolymers as bioactive carriers. This study characterized the physical stability (water sorption and state transition behavior) of selected starch and proteins: octenyl succinate–modified depolymerized waxy corn starch (DWxCn), waxy rice starch (DWxRc), phytoglycogen, whey protein concentrate (80%, WPC), whey protein isolate (WPI), and α‐lactalbumin (α‐L) to determine their potential as carriers of bioactive compounds under different environmental conditions. After enzyme modification and particle size characterization, glass transition temperature and moisture isotherms were used to characterize the systems. DWxCn and DWxRc had increased water sorption compared to native starch. The level of octenyl succinate anhydrate (OSA) modification (3% and 7%) did not reduce the water sorption of the DWxCn and phytoglycogen samples. The Guggenheim–Andersen–de Boer model indicated that native waxy corn had significantly (P < 0.05) higher water monolayer capacity followed by 3%‐OSA‐modified DWxCn, WPI, 3%‐OSA‐modified DWxRc, α‐L, and native phytoglycogen. WPC had significantly lower water monolayer capacity. All Tg values matched with the solid‐like appearance of the biopolymers. Native polysaccharides and whey proteins had higher glass transition temperature (Tg) values. On the other hand, depolymerized waxy starches at 7%‐OSA modification had a “melted” appearance when exposed to environments with high relative humidity (above 70%) after 10 days at 23 °C. The use of depolymerized and OSA‐modified polysaccharides blended with proteins created more stable blends of biopolymers. Hence, this biopolymer would be suitable for materials exposed to high humidity environments in food applications.  相似文献   
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This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.  相似文献   
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