Interactions between milk proteins and polyphenols: Binding mechanisms,related changes,and the future trends in the dairy industry

The biological activity and techno-functional properties of phenolic compounds have gained great importance due to the epidemiologically-proved health benefits. Use of polyphenols as fortification agents for functional food production and nanotechnological approaches using natural vehicles for polyphenol delivery have been recently discussed. In this respect, milk proteins and dairy products represent unique characteristics for polyphenol studies. The conflicting results on the functionality of polyphenols interacting with milk proteins either in model systems or in complex dairy matrices reveal the need for future studies.     

Gabapentin-induced coma in a patient with renal failure

We describe a 60-year-old woman who became comatose after a single dose of gabapentin for right-sided sciatalgia. The patient was improved by hemodialysis. Gabapentin toxicity should be considered when mental status changes develop in patients with renal failure after even a single dose.     

Analysis of dragline cycle time components

This paper focuses on the breakdown of dragline cycle time. A 15-year old dragline deployed for casting the interburden and extracting the coal seam immediately beneath is monitored for a period of 45 days. The following operational modes are sampled: key-cutting, main-cutting, chopping and coal extraction. Data are handled regarding the parameters which have influence on particular stages of a cycle. It has been revealed that bucket loading is influenced by dimensions and geometry of the excavation face, material diggability, spatial position of ground penetration point and operator preference. Dumping phase appears to be affected by bucket fill factor and operator preference. Loaded and empty swing times are positively correlated with associated swing angles. Angular velocity of draglines is low at swing angles of up to 60 degrees. Loaded swing phases appear to be operator-dependent. Bucket repositioning phase is affected by geometry of the excavation area and the position of bucket penetration point. It is independent from the operator preferences.     

ARMA based approaches for forecasting the tuple of wind speed and direction

Short-term forecasting of wind speed and direction is of great importance to wind turbine operation and efficient energy harvesting. In this study, the forecasting of wind speed and direction tuple is performed. Four approaches based on autoregressive moving average (ARMA) method are employed for this purpose. The first approach features the decomposition of the wind speed into lateral and longitudinal components. Each component is represented by an ARMA model, and the results are combined to obtain the wind direction and speed forecasts. The second approach employs two independent ARMA models – a traditional ARMA model for predicting wind speed and a linked ARMA model for wind direction. The third approach features vector autoregression (VAR) models to forecast the tuple of wind attributes. The fourth approach involves employing a restricted version of the VAR approach to predict the same. By employing these four approaches, the hourly mean wind attributes are forecasted 1-h ahead for two wind observation sites in North Dakota, USA. The results are compared using the mean absolute error (MAE) as a measure for forecasting quality. It is found that the component model is better at predicting the wind direction than the traditional-linked ARMA model, whereas the opposite is observed for wind speed forecasting. Utilizing VAR approaches rather than the univariate counterparts brings modest improvement in wind direction prediction but not in wind speed prediction. Between restricted and unrestricted versions of VAR models, there is little difference in terms of forecasting performance.     

Fuzzy multiple-criteria decision-making: Application to AML project selection

ABSTRACT

In this paper, we present the application of fuzzy multiple-criteria decision-making to the problem of abandoned mine land (AML) project selection. More specifically, the category of multiple-criteria techniques known as fuzzy ranking methods are used to rank projects under conditions where the criteria of selection are imprecisely defined and the project scores for the criteria are subjectively determined.

An experiment was designed in which 14 experts contributed their knowledge of AML project criteria to the fuzzy ranking methods through three questionnaires. The first two questionnaires provided the essential information for the methods to form a fuzzy mathematical ranking relationship. The third questionnaire then provided the experts' scores for each of the chosen criteria for eleven candidate reclamation projects chosen from Pennsylvania's AML project inventory. In addition, the third questionnaire also sought overall project rankings from the experts to compare with the rankings provided by the fuzzy ranking methods.

The results appear to prove that fuzzy rankings methods can satisfactorily rank projects of this type and will generally produce results similar to that produced by the experts. While not necessarily better than human rankings, the rankings of the mathematical methods may increase the objectivity in decision-making even though bias in the original data cannot be eliminated.     

An exploratory study of disaggregated clearing functions for production systems with multiple products

Clearing functions (CFs) have shown considerable promise for representing production capacity in production planning models due to their ability to capture the non-linear relationships between throughput, order releases and lead times. Most CFs developed to date use the total work in progress of all products, in units of processing time, as the state variable. In this paper, we investigate CFs for multi-product systems where the overall throughput of the system is affected by the product mix. We show that the aggregate work in process (WIP) variable used in the previous CF literature may lead to inaccurate estimates of expected throughput for individual products. To address this issue, we explore the use of multi-dimensional CFs (MDCFs) that use an extended definition of resource state based on the disaggregated WIP levels for individual products. Several new functional forms for MDCFs are postulated for single machine multi-product systems and their ability to represent system behaviour is assessed using simulation experiments. Results reveal that MDCFs are better able to predict system performance in the presence of mix-dependent capacity losses. We also discuss the extension of the MDCF approach to multi-stage production systems.     

Understanding Chemical Expansion in Non‐Stoichiometric Oxides: Ceria and Zirconia Case Studies

Atomic scale computer simulations, validated with experimental data, are used to uncover the factors responsible for defect‐induced chemical expansion observed in non‐stoichiometric oxides, exemplified by CeO₂ and ZrO₂. It is found that chemical expansion is the result of two competing processes: the formation of a vacancy (leading to a lattice contraction primarily due to electrostatic interactions) and the cation radius change (leading to a lattice expansion primarily due to steric effects). The chemical expansion coefficient is modeled as the summation of two terms that are proportional to the cation and oxygen radius change. This model introduces an empirical parameter, the vacancy radius, which can be reliably predicted from computer simulations, as well as from experimental data. This model is used to predict material compositions that minimize chemical expansion in fluorite structured solid oxide fuel cell electrolyte materials under typical operating conditions.     

Discrete element analysis of experiments on mixing and stoking of monodisperse spheres on a grate

Understanding the details of the mixing and stoking process on grate firing systems is crucial for the optimization of the combustion process in waste or biomass incineration plants. The Discrete Element Method (DEM) can help to obtain further information on the mixing process within a bed of fuel particles. Especially the influence of a change in operational parameters can be examined avoiding large experimental effort. In the current paper five simulations for a generic grate are compared with the corresponding experiments. The experiments were carried out throughout an anterior parameter study on mixing and stoking on a grate [Sudbrock F.; Simsek E.; Wirtz S.; Scherer V.: “An experimental analysis of the influence of operational parameters on mixing and stoking of a monodisperse granulate on a grate”, Powder Technology 198, Issue 1, 29-37, 2010] [19]. The system considered is equipped with vertically moving bars which induce stoking. In a first approach monodisperse plastic spheres are used. The grate is encased by a transparent polycarbonate housing which provides optical access to the movement of the particles in the wall planes. The mixing process is measured and quantified by image analysis of the front wall of the grate. The mixing behaviour of the particle assembly observed in experiments and simulation appears to be very similar indicating that DEM is able to predict the particle mixing in the bed. In order to quantify the visual observations the mixing behaviour has been evaluated by different mixing parameters. They are compared in dependence of the number of strokes of the grate bars. A good agreement between measurements and simulations could be observed.