Proteins from different sources serve as primary food components, while polyphenols, as secondary metabolites, are abundantly present in plant. Both components play an important role in functional ...properties and quality of food products. Interaction between proteins and polyphenols, yielding “protein-polyphenol conjugate”, spontaneously occurs in most of food systems, and is known to have an impact on sensorial, functional, and nutraceutical properties of the food products.
Protein-polyphenol conjugate can be implemented for improvement of food quality. In this article, mechanism and factors affecting protein-polyphenol interactions as well as the functionalities of protein-polyphenol conjugates, especially solubility, thermal stability, emulsifying, gelling and antioxidant properties, are revisited. The information on potential applications of protein-polyphenol conjugates in emulsions, protein-based films, and protein gels, as well as conjugates-based delivery systems is also discussed and reviewed.
The interaction of proteins and polyphenols mainly results from non-covalent (H-bonding, electrostatic interactions) or covalent bonds taking place mostly based on the oxidation of proteins or polyphenol by enzymatic or non-enzymatic pathways. Moreover, protein-polyphenol interaction greatly depends on environmental conditions such as temperature and pH as well as on the conformation or type of proteins and polyphenols. The protein-polyphenol conjugates with higher thermal stability, antioxidant activities, better emulsifying properties and enhanced gelling property can be used as novel food additives for improvement of functionalities and quality of food products.
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•Protein-polyphenol conjugate is formed by non-enzymatic or enzymatic reactions.•Environmental factors and type of polyphenol or protein mainly affect the interaction.•Protein-polyphenol conjugate shows the superior emulsifying and antioxidant activity.•Protein-polyphenol conjugate with higher protein-crosslinks shows improved gelation.
•An extensive number of Machine Learning algorithms using default hyperparameter are proposed to estimate the coefficient of chloride diffusion of concrete including Supplementary Cementitious ...Materials (SCMs).•Gradient Boosting algorithm is the most effective Machine Learning algorithm for chloride diffusion coefficient prediction.•SHAP, Individual Conditional Expectation and Partial Dependence Plot 2D quantify factors’ influence on the chloride diffusion coefficient.
Chloride diffusion coefficient is an important durability indicator in durability design of concrete structure according to performance-based approach. However, this indicator is difficult to anticipate and design due to a variety of factors such as mix design of concrete, the replacement of supplemental cementitious materials (SCMs), and binder selection. This study proposes an extensive number of machine learning algorithms to predict the chloride diffusion coefficient of concrete containing Supplementary Cementitious Materials (SCMs) such as silica fume, ground granulated blast furnace slag, and fly ash. A database containing nine input variables is created, eight machine learning models consisting of Support Vector Machine (SVM), Extreme Learning Machine (ELM), K-Nearest Neighbors (KNN), Light Gradient Boosting (LGB), Extreme Gradient Boosting (XGB), Random Forest (RF), Gradient Boosting (GB), AdaBoost (AdB) are evaluated via performance criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), coefficient of correlation ® and Root Mean Square Error (RMSE). Gradient Boosting model has highest performance in prediction of chloride diffusion coefficient. SHapley Additive exPlanations (SHAP), Individual Conditional Expectation ICE and Partial Dependence Plot PDP 2D allow the most influential inputs to be identified, quantify the influence of input variables on chloride diffusion of concrete. Selection of the best ML algorithm Gradient Boosting is useful to develop a dependable soft computing tool in durability design of concrete structure including the mix design optimization and binder selection.
Compressed sensing magnetic resonance imaging (CS-MRI) has provided theoretical foundations upon which the time-consuming MRI acquisition process can be accelerated. However, it primarily relies on ...iterative numerical solvers, which still hinders their adaptation in time-critical applications. In addition, recent advances in deep neural networks have shown their potential in computer vision and image processing, but their adaptation to MRI reconstruction is still in an early stage. In this paper, we propose a novel deep learning-based generative adversarial model, RefineGAN, for fast and accurate CS-MRI reconstruction. The proposed model is a variant of fullyresidual convolutional autoencoder and generative adversarial networks (GANs), specifically designed for CS-MRI formulation; it employs deeper generator and discriminator networks with cyclic data consistency loss for faithful interpolation in the given under-sampled k-space data. In addition, our solution leverages a chained networkto further enhance the reconstruction quality. RefineGAN is fast and accurate-the reconstruction process is extremely rapid, as low as tens of milliseconds for reconstruction of a 256 × 256 image, because it is one-way deployment on a feed-forward network, and the image quality is superior even for extremely low sampling rate (as low as 10%) due to the data-driven nature of the method. We demonstrate that RefineGAN outperforms the state-of-the-art CS-MRI methods by a large margin in terms of both running time and image quality via evaluation using several open-source MRI databases.
New neutral nickel and palladium ethylene polymerization catalysts have been prepared that incorporate an anionic (N,O) chelating ligand. Extensive axial shielding is provided by two 3,5-dichloroaryl ...moieties in a “sandwich” orientation. Such shielding results in an exceptionally slow rate of chain transfer relative to migratory insertion in the nickel catalyst, and thus highly controlled polymerization of ethylene is observed, leading to lightly branched ultra-high molecular weight polyethylene with M n values up to 4.1 × 106 g/mol. The analogous palladium catalysts provide the means for a detailed mechanistic study of chain propagation in an electronically asymmetric neutral palladium catalyst. Both isomers of the methyl ethylene complex can be generated and observed at low temperatures allowing experimental elucidation of mechanistic details of chain propagation probed in other electronically asymmetric systems only through DFT studies or by examination of model studies. The barrier to migratory insertion in these complexes is ca. 19.2 kcal/mol. Investigation of the equilibration of the methyl ethylene isomers in the presence of excess ethylene showed the isomerization rate is dependent on ethylene concentration. This is the first direct proof that isomerization in these alkyl ethylene intermediates is catalyzed by ethylene. Furthermore, isomer equilibration is much faster than migratory insertion so that the barriers for insertion of individual isomers cannot be determined.
•Machine learning techniques predict compressive strength of concrete made with RAC.•GB_PSO is the best Machine Learning model for prediction of compressive strength.•Mix design of concrete made with ...RAC can be estimated with aided of PDP 1D.
To reduce the environmental impact of construction and demolition waste of concrete, recycled concrete aggregate (RCA) has been widely utilized in concrete. The compressive strength of recycled concrete is one of the most important parameters governing the quality of concrete. The compressive strength is determined from the compression test, which requires a huge amount of materials as well as consumes cost and time. Thus, to solve those limitations, this study focused on evaluating the compressive strength of concrete made from RCA using different single and hybrid models of machine learning. Six machine learning models including Gradient Boosting (GB), Extreme Gradient Boosting (XGB), Support Vector Regression (SVR), and three hybrid models of those single models with Particle Swarm Optimization (PSO) namely GB_PSO, XGB_PSO, and SVR_PSO were used to estimate the compressive strength of recycled concrete. The input variables for modeling consisted of cement content, water content, aggregate content, natural aggregate content, recycle concrete aggregate content, sand content, water absorption rates of natural aggregate and RCA. The results of this study show that hybrid models performed better than single models in terms of prediction accuracy. The results indicated that the GB_PSO has the highest prediction accuracy with R = 0.9356, RMSE = 5.5604 MPa, and MAE = 4.2882 MPa. The results of feature importance analysis and partial dependence plots (PDP) analysis revealed that the most important variable effect on compressive strength of concrete made with RAC is cement content, whatever performance strategies of concrete made with RAC. From the results of PDP, the quantity of each material can be computed easily for the designed compressive strength. In the end, this study provides a systematic evaluation of the compressive strength prediction of recycled concrete and has a significant contribution to literature and practice.
Purpose
The purpose of this paper is to challenge the influence of organisational culture types on leadership behaviour and job satisfaction. The theory of culture was divided into four ...characteristics, namely, clan, hierarchy, adhocracy and market.
Design/methodology/approach
A purposive questionnaire was adapted to collect surveys from 294 working people in several sector organisations in Vietnam. The questionnaire included two main parts. The first part comprising demographic questions. The second part included three constituted scales to evaluate organisational culture types, leadership behaviour and job satisfaction. Correlation and linear regression analysis were adapted to use to challenge connections among variables.
Findings
Hierarchy culture negatively connected to relationship-oriented leadership behaviour. Adhocracy culture positively affected job satisfaction. Clan and market cultures insignificantly predicted leadership style and job satisfaction.
Research limitations/implications
The research is structured in 294 working people in various Vietnamese sector organisations. This small sample is unlikely to represent the popularity of the findings. Further research should collect samples in more organisations and industries in Vietnam to improve the efficiency of the results. The research findings may support leaders and superiors to choose a proper organisational culture that will reduce employee dissatisfaction.
Originality/value
The research is conducive to the studies on organisational culture, especially the association between leadership behaviour and job satisfaction in Vietnamese sector organisations
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Duck albumen hydrolysates (DAH) conjugated with epigallocatechin gallate (EGCG) at various levels (2–5%, w/w) were prepared and characterized. FTIR analysis showed that the ...conjugation between DAH and EGCG induced the change of secondary structure and modified functional groups of DAH. Furthermore, surface hydrophobicity of DAH was increased, while total sulfhydryl group and total carbonyl contents were decreased when EGCG was conjugated, especially when EGCG at higher levels was used (P < 0.05). Antioxidant activities and emulsifying properties of DAH-EGCG conjugates were enhanced, particularly when DAH conjugated with 4% EGCG (P < 0.05). Storage stability of fish oil emulsion (FOE) stabilized by DAH or DAH-EGCG conjugate was also investigated up to 15 days at 26–28 °C. Emulsion stabilized by DAH-EGCG conjugate had higher magnitude of ζ-potential (negative charge), smaller oil droplets size (d43), as well as lower flocculation and coalescence of oil droplets as compared to those of emulsion prepared using DAH throughout the storage. Moreover, oxidative stability of FOE was improved when DAH-EGCG conjugate was incorporated as evidenced by lowered thiobarbituric acid-reactive substances and peroxide value. Thus, the conjugate between DAH and 4% EGCG could serve as an antioxidant emulsifier for enhancement of physical and oxidative stability of FOE.
Summary
Influences of different ultrasound treatments combined with heat pretreatment on enzymatic hydrolysis, emulsifying properties and antioxidant activities of hydrolysates from duck egg albumen ...were studied. Heat pretreatment at 95 °C for 30 min inhibited both serine and cysteine protease inhibitors effectively. Ultrasonication of heated duck albumen at 60% amplitude for 10 min yielded the highest surface hydrophobicity. Coincidentally, aforementioned pretreatment rendered the hydrolysate with highest degree of hydrolysis (DH) than other pretreatments when Alcalase was used. The resulting hydrolysate showed the highest antioxidant activities including DPPH radical and ABTS radical cation scavenging activities and ferric reducing antioxidant power as well as emulsifying properties when hydrolysis time of 90 min was used. The hydrolysate possessed the peptides with molecular weight of 219–255 Da with the highest ABTS radical scavenging activity. Thus, heat pretreatment, followed by ultrasonication of duck albumen under appropriate condition could increase DH, antioxidant activities and emulsifying properties of duck albumen hydrolysate.
Production and characterization of duck albumen hydrolysate using enzymatic process.
Along with the increased installation of distributed energy resources (DER), long‐term voltage stability can be improved if proper coordination is developed between DERs and grid controllers, for ...example, Load Tap Changer (LTC). In most of the proposed methods, the steady‐state voltage‐sensitivity analysis has been implemented to predict the voltage state, which is the state's dynamic evolution in abnormal operations of the grid with high shares of DERs. This paper presents a system identification‐based model predictive control (MPC), which can coordinate DERs and LTC to restore the voltage to the pre‐fault condition after emergencies. First, the online voltage evolution is predicted based on the sparse identification of the nonlinear dynamics (SINDY) technique. Then, the SINDY‐based voltage prediction is combined with an adaptive MPC in the centralized controller. In addition, the nonlinear of DERs have been modeled to avoid the MPC‐based coordination jeopardizing the local constraints of DERs. The proposed method has been tested in a modified CIGRE benchmark network. Simulation results show that the dynamic voltage is effectively estimated by the SINDY method. Furthermore, the developed MPC model smoothly supports faster voltage recovering time with the least number of control actions of LTCs.
Summary Background Malignant pleural mesothelioma is an aggressive cancer with poor prognosis, linked to occupational asbestos exposure. Vascular endothelial growth factor is a key mitogen for ...malignant pleural mesothelioma cells, therefore targeting of vascular endothelial growth factor might prove effective. We aimed to assess the effect on survival of bevacizumab when added to the present standard of care, cisplatin plus pemetrexed, as first-line treatment of advanced malignant pleural mesothelioma. Methods In this randomised, controlled, open-label, phase 3 trial, we recruited patients aged 18–75 years with unresectable malignant pleural mesothelioma who had not received previous chemotherapy, had an Eastern Cooperative Oncology Group performance status of 0–2, had no substantial cardiovascular comorbidity, were not amenable to curative surgery, had at least one evaluable (pleural effusion) or measurable (pleural tumour solid thickening) lesion with CT, and a life expectancy of >12 weeks from 73 hospitals in France. Exclusion criteria were presence of central nervous system metastases, use of antiaggregant treatments (aspirin ≥325 mg per day, clopidogrel, ticlopidine, or dipyridamole), anti-vitamin K drugs at a curative dose, treatment with low-molecular-weight heparin at a curative dose, and treatment with non-steroidal anti-inflammatory drugs. We randomly allocated patients (1:1; minimisation method used random factor of 0·8; patients stratified by histology epithelioid vs sarcomatoid or mixed histology subtypes, performance status score 0–1 vs 2, study centre, or smoking status never smokers vs smokers) to receive intravenously 500 mg/m2 pemetrexed plus 75 mg/m2 cisplatin with (PCB) or without (PC) 15 mg/kg bevacizumab in 21 day cycles for up to six cycles, until progression or toxic effects. The primary outcome was overall survival (OS) in the intention-to treat population. Treatment was open label. This IFCT-GFPC-0701 trial is registered with ClinicalTrials.gov , number NCT00651456. Findings From Feb 13, 2008, to Jan 5, 2014, we randomly assigned 448 patients to treatment (223 50% to PCB and 225 50% to PC). OS was significantly longer with PCB (median 18·8 months 95% CI 15·9–22·6) than with PC (16·1 months 14·0–17·9; hazard ratio 0·77 0·62–0·95; p=0·0167). Overall, 158 (71%) of 222 patients given PCB and 139 (62%) of 224 patients given PC had grade 3–4 adverse events. We noted more grade 3 or higher hypertension (51 23% of 222 vs 0) and thrombotic events (13 6% of 222 vs 2 1% of 224) with PCB than with PC. Interpretation Addition of bevacizumab to pemetrexed plus cisplatin significantly improved OS in malignant pleural mesothelioma at the cost of expected manageable toxic effects, therefore it should be considered as a suitable treatment for the disease. Funding Intergroupe Francophone de Cancérologie Thoracique (IFCT).
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