The rheological properties and microstructure of doughs, and the texture properties of whole wheat breads and noodles were investigated. The gluten strength of doughs were discriminated due to wheat cultivar. Reduced flour particle size led to the doughs with a stronger gluten strength (i.e., smaller C2), lower degree of starch retrogradation (i.e., smaller C5), and longer relaxation time (i.e., larger n values). Firmer crumb of breads were prepared by flours with smaller particle size. With increased bran content, the gluten strength of dough weakened (i.e., increased C2), the development and relaxation time of dough and the degree of starch retrogradation decreased (i.e., decreased C1 time, n values and C5), the dough structure became more porous, and the product texture appeared to be firmer. As such, outcomes from this research will provide a practical guidance for the bakery industry to improve the consumer acceptability of whole wheat products.
The stability against various environmental stresses of the curcumin-loaded secondary and tertiary emulsions that was emulsified by whey protein isolate (WPI) and coated by chitosan (CHI), carboxymethyl konjac glucomannan (CMKGM), or their combination through layer-by-layer assembly was investigated. Generally, the multilayered emulsions were destabilized in high NaCl concentrations or medium pH that could interrupt the electrostatic interaction between the three polyelectrolytes or deprotonate CHI, indicating that electrostatic interaction played an important role in the stability of emulsions. Compared with the primary emulsion that was solely stabilized by WPI, extra coating with CHI and CMKGM generally increased the stability of the emulsion against repeated freezing-thawing, improved the retention of curcumin against heating, UV irradiation, and long-term storage, and the effects were more remarkable in the tertiary emulsion with CMKGM locating in the outmost layer. Since CMKGM has shown the colon-targeted delivery potency, the multilayered emulsions assembled by layer-by-layer deposition, especially the tertiary emulsion, could be used as an effective carrier for the targeted delivery of curcumin.
In the present study, the effects of cooked rice (CR) with added fructo-oligosaccharide (FOS) on faecal flora were studied by a simulated in vitro digestion and fermentation method. The total carbohydrate content, pH, and short-chain fatty acids (SCFAs) were determined during in vitro digestion and fermentation. The change in the bacterial phase distribution after the fermentation was also analysed. The results showed that the total carbohydrate content of the CR with added FOS (FCR) significantly decreased during the simulated digestion. Meanwhile, the pH of the FCR decreased and the SCFAs concentration increased significantly compared to those of the CR during the simulated fermentation. In addition, the FCR showed the advantage of promoting beneficial bacteria, such as Bifidobacterium and Lactobacillus, and inhibiting harmful bacteria, such as Bacteroides and Klebsiella compared to the CR. Therefore, the FOS as a prebiotic could be recommended to produce the high-quality healthy rice food.
Most collaborative filtering recommendation algorithms rely too much on the user's historical rating data. However, selection bias is common in explicit feedback data, which makes the learning of user preferences face more challenges. We verify the influence of selection bias on topN recommendation, and propose a data filling strategy using uninteresting items based on temporal visibility to alleviate the selection bias in the data. Specifically, our method includes a weighted matrix factorization model to learn users' pre-use preferences for unrated items. According to the experience of items that users have seen but not interacted show negative preferences, we combine user activity, item popularity and temporal rating information to carry out non-uniform weighting to evaluate the confidence of unrated items as a negative example. Then the items with low pre-use preferences are taken as uninteresting items and filled in a low value to restore the user's real rating distribution. Experiments on two real world datasets show that our algorithm can effectively alleviate the selection bias and improve the recommendation accuracy.
The colorimetric sensor array real-time monitoring system with multivariate analysis was established for discrimination of potato varieties with different types and degrees of corruption. The characteristic volatile compounds of fresh, dry rot and soft rot potatoes was identified by Gas Chromatography-Mass Spectrometry and the 3 × 4 array was fabricated to capture the characteristics volatile compounds. The sensor array system produced a visible color difference map upon its exposure to volatile compounds of potato. Discrimination of potatoes with the same types or different degrees of corruption was subsequently achieved using principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbor algorithm for potato classification provided the best results with 100 % discrimination on both the calibration and prediction sets. The linear discriminant analysis model achieved a 99.76 % calibration set and a 99.31 % prediction set for potato grading. An online warning device based on array was devised to realize unmanned monitoring for potato quality.
The long-term storage of rice will inevitably be involved in the deterioration of edible quality, and aged rice poses a great threat to food safety and human health. The acid value can be employed as a sensitive index for the determination of rice quality and freshness. In this study, near-infrared spectra of three kinds of rice (Chinese Daohuaxiang, southern japonica rice, and late japonica rice) mixed with different proportions of aged rice were collected. The partial least squares regression (PLSR) model with different preprocessing was constructed to identify the aged rice adulteration. Meanwhile, a competitive adaptive reweighted sampling (CARS) algorithm was used to extract the optimization model of characteristic variables. The constructed CARS-PLSR model method could not only reduce greatly the number of characteristic variables required by the spectrum but also improve the identification accuracy of three kinds of aged-rice adulteration. As above, this study proposed a rapid, simple, and accurate detection method for aged-rice adulteration, providing new clues and alternatives for the quality control of commercial rice.
Recently, aviation pollution has drawn important social attention. The protocol proposed in this paper can simultaneously calculate the overall emissions of six aviation pollutants (CO2, CO, HC, NOx, SO2, and PM2.5), including the landing and take-off emissions and climb/cruise/descent emissions. The international routes in South America during 2019–2021 are an example to illustrate the use of this protocol. This protocol can provide a methodological basis for calculating aviation pollutant emissions in different countries and regions. For complete details on the use and execution of this protocol, please refer to Cui et al. (2022b).
Whole wheat flour dough (WWFD) has a high content of dietary fibres that causes a negative influence on the dough rheology, resulting in undesirable quality for whole wheat bread (WWB). Therefore, to devise the processing strategies for overcoming the quality issues for WWB is of remarkable significance. The cooperative fermentation by yeast and lactic acid bacteria (CFYL) has been proposed as a powerful processing technology to modify the dough rheology, retention and stabilization of gas cells for a WWFD. The breadmaking performance of WWFD has been modified due to the CFYL-induced changes in the structure of wheat bran, gluten proteins and wheat starch. CFYL mitigated the negative influence of wheat bran on gluten network. CFYL also strengthened the intermolecular interactions between proteins and starch. During CFYL, exopolysaccharides (EPSs), enzymes and organic acids were produced which modified the dough rheology and led to an improvement in the bread quality. Moreover, CFYL contributed to an increase in the water-extractable arabinoxylans and soluble wheat proteins but a decrease in the starch granule sizes. This results in a higher strain hardening and a stronger liquid film of the dough for improving the retention and stabilization of gas cells in a WWFD during breadmaking. As such, CFYL has a good potential use for WWB manufacturing to achieve the products with desirable overall quality and satisfactory consumer acceptability.
Digital technology has created new elements of innovation types and given incumbent firms new portfolios of innovation. The portfolio of innovation used during a digital transformation allows it to be successfully implemented and gives a competitive advantage to incumbent firms. We present two propositions for the portfolio of innovation and its shift during the process of digital transformation. Based on an emergent innovation matrix, we conducted a multi-case study on three Chinese firms from different industries, in order to identify the novel innovation types that appear when these firms undergo digital transformation. The research suggests that incumbent firms innovate in various ways simultaneously to implement a digital transformation when faced with market and technology change, and the portfolio of innovation shifts during the digital transformation process.
In this study, the self-developed caffeic acid-grafted-chitosan/polylactic acid (CA-g-CS/PLA) film was applied to the preservation of Agaricus bisporus, and the potential mechanism of retarding its quality loss through regulation of essential genes was further explored. The results of transcriptome analysis showed that CA-g-CS/PLA packaging could regulate essential genes involved in membrane lipid metabolism and energy metabolism to delay the decrease in unsaturated fatty acids, energy loss and reactive oxygen species (ROS) accumulation by decreasing the respiration rate of A. bisporus. In addition, the expression of SHO1 and wis1 related to mitogen-activated protein kinase (MAPK) signalling in the CA-g-CS/PLA group of A. bisporus was increased, which indicated that the osmotic balance could be better maintained. Therefore, CA-g-CS/PLA packaging could improve the quality of postharvest A. bisporus by regulating the essential genes related to the pathway of membrane lipid metabolism, energy and ROS metabolism, and MAPK signalling transduction.
In the era of internet-based information, how to promote sustainable low-carbon consumption by residents through information incentives and social influence is a pressing question that needs to be solved urgently. This study develops an explanatory model to explain how information incentives and social influence affect sustainable low-carbon consumption by residents. Data were collected from residents by large-scale online surveys in China. Partial least squares (PLS) regression was used to evaluate the model in its theory-mediated model scope to make it better than multiple regression. The empirical results show that purchase behavior, daily use behavior, waste disposal behavior, and public participation behavior define sustainable low-carbon consumption behavior; information incentives and social influence are two important predictors for low-carbon consumption behavior; at the level of information motivation, emotional information has a greater impact on low-carbon consumption behavior than rational information; and at the level of social influence, the influence of peer imitation is greater than that of endorsements and social norms. This study provides interesting insights into the important role of information and social networks for promoting low-carbon consumption behavior. Finally, we propose an information-based guidance policy to promote low-carbon consumption behavior based on social influence.
The scale of China’s digital economy has accounted for over one-third of the total GDP. How this development impacts the wage rates of both genders and, therefore, reshapes the pattern of gender wage rates discrimination? Using the 2018 urban data from the Chinese Household Income Project as a sample, this study comprehensively employed the Mincer wage determination, Oaxaca–Blinder decomposition and moderating effect models to examine the role of working hours (WHs) in developing the gender wage rate gap (WRG) and to analyse the heterogeneous impact of the digital economy. The study deduced that relatively longer WHs of men compared to those of women helped narrow the gender WRG by 16%. However, relatively higher rate of return for men widened the gender WRG by 14%–19%. The prospering digital economy has not significantly changed the pattern of WHs between genders and will not significantly impact the endowment effect. However, it may increase the wage rate for women, ironing out the discriminatory effect faced by both genders on the dimension of WHs. We can focus on reducing the digital divide by guiding the diffusion of digital economy elements to weak areas and vulnerable groups and providing more active and sufficient digital skills training for women, especially those employed in low- and medium-skilled jobs. These measures will help reduce the gender WRG, promote ‘equal pay for equal work’ and realise the positive outcomes of the iron-out effect of the digital economy on the discrimination effect of WHs.
In the era of big data, data-driven services (DDS) have become critical competitive strategies for digital platform-based enterprises. This paper considers two operational modes of e-commerce platforms, which are self-operated and third-party modes, respectively, and they each lead a platform system. The Hotelling model is adopted to describe the competitive market of both platforms. We characterize their system performance functions. The optimization models are built using game theory to discuss the DDS and price decisions. We obtain the implementation conditions of DDS strategies for both platforms and the dominant situations of their respective DDS levels. We find that a platform adopting the price reduction strategy can improve the performance of its platform system while reducing the competitor’s system performance. From the system performance perspective, continuous improvement of the DDS level may appear “harming others may not benefit oneself”; that is, continuously improving the DDS level leads to a decrease in the competitor’s system performance but not necessarily an increase in its system performance. Further, consumer welfare within both platform systems shows the law of “as one falls then another rises”. As the big data industry matures, self-operated platforms would demonstrate the advantages of service level, profit, and system performance. In contrast, third-party platforms would have an advantage in consumer welfare. These conclusions have important implications for e-commerce platforms developing data-driven operations-based strategies.
This article studies a mean-variance portfolio selection problem for a jump-diffusion model, where the drift process is modulated by a continuous unobservable Markov chain. Since there is a constraint on wealth, we tackle this problem via the technique of martingale. We first investigate the full information case that the Markov chain can be observable, closed-form expressions not only for the optimal wealth process and optimal portfolio strategy but for the efficient frontier are derived. Then, by the filtering theory, we reduce the original partial information problem to a full information one, and the corresponding optimal results are obtained as well. Furthermore, if short selling is not allowed, we find that the solution in the full information case can be derived by transforming the problem into an equivalent one with constraint only on wealth, but this technique is not applicable anymore for the partial information case.
The common spatial patterns (CSP) technique is an effective strategy for the classification of multichannel electroencephalogram (EEG) signals. However, the objective function expression of the conventional CSP algorithm is based on the L2-norm, which makes the performance of the method easily affected by outliers and noise. In this paper, we consider a new extension to CSP, which is termed capped L21-norm-based common spatial patterns (CCSP-L21), by using the capped L21-norm rather than the L2-norm for robust modeling. L21-norm considers the L1-norm sum which largely alleviates the influence of outliers and noise for the sake of robustness. The capped norm is further used to mitigate the effects of extreme outliers whose signal amplitude is much higher than that of the normal signal. Moreover, a non-greedy iterative procedure is derived to solve the proposed objective function. The experimental results show that the proposed method achieves the highest average recognition rates on the three real data sets of BCI competitions, which are 91.67%, 85.07%, and 82.04%, respectively. Graphical abstractCapped L21-norm-based common spatial patterns—a robust model for EEG signals classification
Drought-flood abrupt alternation (DFAA) as a compound natural disaster can cause severe socioeconomic loss and environmental destruction. Under climate change, the Huang-Huai-Hai River Basin has experienced evident increases in temperature and variability of precipitation. However, the study of the evolution characteristics of DFAA in the Huang-Huai-Hai River Basin is limited and the risk of exposure to DFAA events under future climatic conditions should be comprehensively assessed. In this study, the DFAA events including drought to flood (DTF) and flood to drought (FTD) events in the Yellow River Basin (YRB), Huai River Basin (HuRB), and Hai River Basin (HaRB) are identified by the long-cycle drought-flood abrupt alternation index (LDFAI) and the temporal variation and spatial distribution of the number and intensity of DFAA events from 1961 to 2020 are examined. The 24 climate model simulations of Coupled Model Intercomparison Project Phase 6 (CMIP6) are used to evaluate the variation of DFAA events based on the bias-corrected method. The results show that both DTF and FTD events occurred >10 times in most areas of the Huang-Huai-Hai River Basin from 1961 to 2020, and severe DFAA events occurred more frequently in the HaRB. The occurrence of DTF events decreased and FTD events continuously increased in the YRB, while they showed opposite trends in the HuRB and HaRB. In the future, the Huang-Huai-Hai River Basin is projected to experience more DTF events under the SSP1-2.6 and SSP2-4.5 scenarios, while more FTD events under the SSP3-7.0 and SSP5-8.5 scenarios. Most areas in the Huang-Huai-Hai River Basin are projected to be at medium or high risk of the frequency and intensity of DFAA events under different future scenarios, especially in the central part of the YRB. These findings can provide scientific reference to the formulation of management policies and mitigation strategies.
In the process of China’s modernization, promoting the sustainable development of resource-based cities is a major strategic issue and it has now also become a worldwide issue. This study uses the coupling model to validate the coupling relationship between China’s land-use net carbon flux and economic growth and population change during 2009–2017. The study for the first time draws the conclusion that the coupling degree among the three is getting lower, the correlation is gradually weaker, and the independent relationship is becoming more and more prominent. Utilizing the Tapio decoupling model, we obtained the weak decoupling conclusion that the economic growth rate is higher than the growth rate of the land-use net carbon flux, while negative decoupling of sprawl is where the rate of population growth is less than the rate of net land-use carbon flux growth.
Social Q&A refers to the process of information seeking based on questioning‐and‐answering in natural language through social networks. It facilitates knowledge gathering and interacting, and thus can be regarded as an appropriate environment for informal learning. This study intends to explore factors affecting continuance intention of using social Q&A communities for informal learning and meanwhile reveal the underlying mechanism among these factors. Data were obtained from 257 university students through an online survey. By using partial least squares based structural equation model, the proposed hypotheses and research model were analyzed. The findings show that homophily, interactivity and social presence are three determinants of collaborative learning and community identification in social Q&A community which further influences university students' continuance intention for informal learning. Our research extends the understanding of informal learning in social Q&A communities and indicates how to promote continuous informal learning in such environment. Collaborative learning and community identification are two influential factors for university students to continuously use social Q&A communities for informal learning. When using social Q&A communities, social presence perceived by university students will promote collaborative learning through community identification. Homophily and interactivity exert significant influences on collaborative learning, community identification, and social presence perceived in social Q&A community. Collaborative learning and community identification are two influential factors for university students to continuously use social Q&A communities for informal learning. When using social Q&A communities, social presence perceived by university students will promote collaborative learning through community identification. Homophily and interactivity exert significant influences on collaborative learning, community identification, and social presence perceived in social Q&A community.
In this paper, we propose an improved algorithm based on the original two-dimensional (2D) multifractal detrended fluctuation analysis (2D MF-DFA) that involves increasing the number of cumulative summations in the computational steps of 2D MF-DFA. The proposed method aims to modify the distribution of the generalized Hurst exponent to ensure that skin lesion image features are extracted based on enhanced multifractal features. We calculate the generalized Hurst exponent using 0, 1, or 2 cumulative summation processes. A support vector machine (SVM) is adopted to examine the classification performance under these three conditions. Computation shows that the process involving two cumulative summations achieves an accuracy, sensitivity, and specificity of [Formula: see text], [Formula: see text], and [Formula: see text], respectively, which indicates that its performance is much better than with 0 and 1 cumulative summations.
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