Predictive Analysis and Simulation Uncertainty of a Distributed Hydrological Model

Distributed hydrological models should pass through a careful calibration procedure backed by sensitivity, uncertainty and predictive analysis before they are utilized as a decision making aid in watershed management and scenario studies. This paper examines whether the uncertainty of the parameters of the spatially distributed hydrologic model WetSpa causes significant uncertainty in the model predictions. The WetSpa model is applied to the Torysa river basin, a rather large catchment located in Slovakia. Parameter estimation, sensitivity and predictive analysis of the model parameters are performed using a model-independent parameter estimator, PEST. It is found that the correction factor for measured evaporation data has the highest relative sensitivity. Parameter uncertainty and predictive analysis give an insight of a proper parameter set and parameter uncertainty intervals and prove that the parameter uncertainty of the model does not result in a significant level of predictive uncertainty.     

A mathematical model and ant colony algorithm for multi-manned assembly line balancing problem

In real-world assembly lines, that the size of the product is large (e.g., automotive industry), usually there are multi-manned workstations where a group of workers simultaneously perform different operations on the same individual product. This paper presents a mixed integer programming model to solve the balancing problem of the multi-manned assembly lines optimally. This model minimizes the total number of workers on the line as the first objective and the number of opened multi-manned workstations as the second one. Since this problem is well known as NP (nondeterministic polynomial-time)-hard, a heuristic approach based on the ant colony optimization approach is developed to solve the medium- and large-size scales of this problem. In the proposed algorithm, each ant tries to allocate given tasks to multi-manned workstations in order to build a balancing solution for the assembly line balancing problems by considering the precedence relations, multi-manned assembly line configuration, task times, and cycle time constraints. Through computational experiments, the performance of the proposed ACO is compared with some existing heuristic on various problem instances. The experimental results validate the effectiveness and efficiency of the proposed algorithm.     

Preparation and characterization of a polyaniline/poly(butyl acrylate–vinyl acetate) composite as a novel conducting polymer composite

This is the first report on the preparation and characterization of a polyaniline/poly(butyl acrylate–vinyl acetate) composite. The composite was prepared by the emulsion polymerization of aniline in a medium containing poly(butyl acrylate–vinyl acetate). Films prepared from the composite (cast from an aqueous medium) had excellent mechanical properties and could be stretched up to 900%. The resultant composite was soluble in common organic solvents, and a stable water‐based dispersion could also be prepared. An electrical conductivity of 2.2 S cm^?1 was obtained. Cyclic voltammograms revealed that the composite was electroactive. It had excellent adhesion to either glass or steel plate. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 2525–2531, 2003     

Synthesis and characterization of cadmium doped lead-borate glasses

Cadmium doped lead-borate glasses were prepared from the melts in appropriate proportions of PbO₂, H₃BO₃ and (15–40 mol%) CdO mixture in the temperature range 700–950°C. The infrared spectra of the glasses in the range 400–4000 cm^-1 show their structures. No boroxol ring formation was observed in the structure of these glasses. Furthermore, doped cadmium atoms were not seen in tetrahedral coordination. But the conversion of three-fold to four-fold coordination of boron atoms in the structure of glasses was observed.     

Changes in blocking mechanisms during membrane processing of pomegranate juice

The effect of pressure, velocity, pretreatment, membrane type and pore size on fouling mechanisms were evaluated. Pomegranate juice was treated with polyvinylidene fluoride (PVDF) 0.22 μm and mixed cellulose ester (MCE) 0.1 μm at different pressures. Cake formation which was the dominant mechanism was formed in the first stages of process and, as the filtration proceeded, intermediate, standard, and complete blocking, respectively occurred at higher pressure (5 kPa). At lower pressure (0.5 kPa) the last mechanism did not occur. Results showed that cake formation was the only mechanism in MCE 0.22 μm, however, others occurred with MCE 0.1 μm and PVDF 0.22 μm. Using MCE 0.22 μm prior to MCE 0.025 μm can reduce the role of cake formation in pore blocking. Evaluation of the impact of velocity showed that at the higher velocity (0.53 m s⁻¹) the complete blocking occurred faster than at the lower velocity (0.09 m s⁻¹).     

Physicochemical evaluation of nanocomposite hydrogels with covalently incorporated poly(vinyl alcohol) functionalized graphene oxide

To avoid the negative effect of graphene oxide (GO) nanosheets aggregation in aqueous solutions on physicochemical properties of GO incorporated nanocomposite hydrogels, poly(vinyl alcohol)-functionalized GO (GO-es-PVA) are synthesized and are used for preparation of nanocomposite hydrogels. By graft copolymerization of GO-es-PVA with poly(AA-co-AAm) chains, the nanocomposite hydrogel samples with covalently incorporated GO-es-PVA are achieved. FTIR spectroscopy, XRD analysis, and SEM and EDAX techniques confirm successful synthesis process. It is clear that GO-es-PVA content has significant effect on physicochemical properties of nanocomposite hydrogels, such as improvement of the water uptake properties, porosity, and gel strength. The hydrogel sample with 1:80 mass ratio of GO-es-PVA/AAm has the best physicochemical properties due to the optimum amount of GO-es-PVA, which gives the hydrogel proper viscoelasticity as well as fine porosity and water uptake rate. Interpenetration of PVA chains into the polymeric networks makes the movement of the polymer chains easier, which leads to softer polymeric networks. This phenomenon is called plasticizing effect. The plasticizing nature of PVA and its high hydrophilicity are the main reasons for the fine physicochemical properties. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48025.     

Nonstationary convective drying of raspberries,assisted by microwaves and ultrasound

This study was conducted to investigate the drying characteristics and quality of raspberries dried in non-stationary conditions. Seven drying programs were carried out, including convective (CV) drying as a reference. The non-stationary-hybrid programs were based on continuous CV drying with intermittent microwave and ultrasound assistance. The Midilli–Kucuk model was used successfully to describe the drying kinetics of raspberry fruits. The comparison between moisture ratio, drying rate, diffusion coefficient, energy consumption, and quality analysis, showed that non-stationary-hybrid drying improves process kinetics and results in less color change, higher anthocyanin retention, and better texture profile analysis characteristics with optimal energy usage than other methods. In addition, the physical and microstructural changes occurred during different drying processes were discussed.     

Prolonged drug release using PCL–TMZ nanofibers induce the apoptotic behavior of U87 glioma cells

In situ prolonged delivery of drugs at the site of tumor can be satisfactorily accelerated patient recovery. We compared the effect of temozolomide while incorporated by polycaprolactone nanofibers on the apoptotic behavior of U87 glioma cells. After biocompatibility evaluation of nanofibers by scanning electron microscope and 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide analysis, the apoptosis of U87 cells was evaluated using p53, Bcl2 and Bax genes expression. It was found that nanofiber-temozolomide group showed a greater ability to induce apoptosis as well as have a significantly diminished initial burst release of drug compared with other groups and have promising potential in treating cancer.     

In-Process Monitoring of Nickel-Based Super Alloy Grinding Using the Acoustic Emission Method

Russian Journal of Nondestructive Testing - One of the most prevalent problems in grinding nickel-based super alloys is grinding wheel loading phenomenon which is the chip accumulation in free...     

A computationally efficient multi-domain active learning method for crop mapping using satellite image time-series

Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide precious information for several agricultural applications, such as crop monitoring, yield forecasting, and crop inventory. However, several issues affect the classification performance of SITS data. As one of the most challenging problems, constituent images of time-series provide different levels of information about crops. These differences are the result of dynamic spectral responses of crops and also the variable atmospheric and sensor conditions. The second issue is the unavailability of adequate high-quality samples for training the classifier. In this study, we proposed a novel computationally efficient Multi-Domain Active Learning (MDAL) method which takes advantage of Multiple Kernel Learning (MKL) and Active Learning (AL) algorithms to address these two issues. The proposed method uses MKL algorithms to address the issues associated with different information level of the data, which generally cannot be modelled using the well-known classification algorithms. AL algorithms were also used for semi-automatic selection of training samples. However, most of the MKL algorithms are very computationally demanding. Consequently, using them in the MDAL method can dramatically increase the computational costs. Thus, in this paper, we presented the similarity-based MKL algorithms. Thanks to their low computational complexities, these algorithms are the most suitable MKL algorithms that can be used in the MDAL method. We evaluated the proposed method using two multispectral SITS datasets, acquired by RapidEye and SPOT sensors. The obtained results of the MDAL method for these datasets respectively showed 8.2% and 5.87% increase in the overall accuracy of classification as compared to the accuracy of the standard AL algorithm. The results also showed that in the case of adopting the SimpleMKL algorithm (a common MKL algorithm in the literature) the computational time of the MDAL method is 577 and 474 seconds for RapidEye and SPOT datasets, respectively. However, in the case of adopting the similarity-based MKL algorithms, these computational times respectively decreases to 4 and 2 seconds.