Improved aqueous solubility,bioaccessibility and cellular uptake of quercetin following pH-driven encapsulation in whey protein isolate

The purpose of this study was to increase the water solubility and potential bioavailability of quercetin by encapsulation in whey protein isolate (WPI) based on a green, efficient pH-driven method. According to the results, the water solubility of quercetin increased by 346.9: times after loading into WPI nanoparticles. When the initial quercetin concentration was 0.25 mg mL⁻¹ and WPI was 2% w/v, the encapsulation efficiency reached 94.1%, the Z-average diameter was 36.63 nm, and the zeta potential was −36.4 mV at pH 7.0. The fluorescence spectroscopy assay suggested the molecular complexation of quercetin and WPI at pH 12.0. X-ray diffraction assay indicated the enclosure of amorphous quercetin in WPI. Correspondingly, the bioaccessibility increased from 2.76% to 31.23% and the Caco-2 cell monolayer uptake increased from 0% to 2.12% after nanoencapsulation. This work confirmed that the pH-driven method is an effective approach to prepare WPI–quercetin nanocapsules to improve physical and potentially biological properties of quercetin.     

Novel pearl millet couscous process for West African markets using a low-cost single-screw extruder

Traditional West African pearl millet couscous products are popular; however, their preparation is laborious, time-consuming and energy-demanding, involving agglomeration, steaming, drying and sieving steps. In this study, a process was developed to produce millet couscous using a high pressure, high temperature and low-cost single-screw extruder. The innovation was to directly process the cooked low-moisture extrudate to a couscous product by drying and milling to the appropriate particle size (ranging between 1 and 2 mm). Throughput for the traditional process as prepared for commercial sale is 50 kg per day, but with the same amount of labour, the extrusion process yields ~350 kg per day. A consumer sensory study held in Niamey (Niger) showed that the extruded millet couscous was comparable to traditional couscous, though this was dependent on selection of the proper millet variety. This novel extrusion process could stimulate small- to medium-scale manufacturing of couscous and couscous-type products in West Africa.     

Evolutionary collective behavior decomposition model for time series data mining

In this research, we propose a novel framework referred to as collective game behavior decomposition where complex collective behavior is assumed to be generated by aggregation of several groups of agents following different strategies and complexity emerges from collaboration and competition of individuals. The strategy of an agent is modeled by certain simple game theory models with limited information. Genetic algorithms are used to obtain the optimal collective behavior decomposition based on history data. The trained model can be used for collective behavior prediction. For modeling individual behavior, two simple games, the minority game and mixed game are investigated in experiments on the real-world stock prices and foreign-exchange rate. Experimental results are presented to show the effectiveness of the new proposed model.     

Hydrocarbon-based electrode ionomer for proton exchange membrane fuel cells

The electrode ionomer is a key factor that significantly affects the catalyst layer morphology and fuel cell performance. Herein, sulfonated poly(arylene ether sulfone)-based electrode ionomers with polymers of various molecular weights and alcohol/water mixtures were prepared, and those comprising the alcohol/water mixture showed a higher performance than the ones prepared using higher boiling solvents, such as dimethylacetamide; this is owing to the formation of the uniformly dispersed ionomer catalyst layer. The relation between ionomer molecular weight for the same polymer structure and the sulfonation degree was investigated. Because the chain length of polymer varies with molecular weight and chain entanglement degree, its molecular weight affects the electrode morphology. As the ionomer covered the catalyst, the agglomerates formed were of different morphologies according to their molecular weight, which could be deduced indirectly through dynamic light scattering and scanning electron microscopy. Additionally, the fuel cell performance was confirmed in the current-voltage curve.     

SINA: Semantic interpretation of user queries for question answering on interlinked data

The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.     

A novel intelligent approach for yaw position forecasting in wind energy systems

Yaw control systems orientate the rotor of a wind turbine into the wind direction, optimize the wind power generated by wind turbines and alleviate the mechanical stresses on a wind turbine. Regarding the advantages of yaw control systems, a k-nearest neighbor classifier (k-NN) has been developed in order to forecast the yaw position parameter at 10-min intervals in this study. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters are used in 2, 3, 4, 5 and 6-dimensional input spaces. The forecasting model using Manhattan distance metric for k = 3 uncovered the most accurate performance for atmosphere pressure, wind direction, wind speed and rotor speed inputs. However, the forecasting model using Euclidean distance metric for k = 1 brought out the most inconsistent results for atmosphere pressure and wind speed inputs. As a result of multi-tupled analyses, many feasible inferences were achieved for yaw position control systems. In addition, the yaw position forecasting model developed was compared with the persistence model and it surpassed the persistence model significantly in terms of the improvement percent.