Utilization of saffron (<Emphasis Type="Italic">Crocus sativus L.</Emphasis>) as sensitizer in dye-sensitized solar cells (DSSCs)

Photoelectrodes of dye-sensitized solar cells (DSSCs) have been prepared using nanosized titanium dioxide that have soaked in a solution of different saffron (Crocus sativus L.) spice content in ethanol. The optimized polyacrylonitrile (PAN)-based gel polymer electrolyte with 40.93 wt.% ethylene carbonate, 37.97 wt.% propylene carbonate, 4.37 wt.% tetrapropylammonium iodide, 9.86 wt.% PAN, 1.24 wt.% 1-butyl-3-methylimidazolium iodide, 4.35 wt.% lithium iodide and 1.28 wt.% iodine has been used as the electrolyte for DSSC. The electrolyte has conductivity of 2.91 mS cm^?1 at room temperature (298 K). DSSCs were also sensitized with saffron solution that has been added with 30 wt.% chenodeoxycholic acid (CDCA) co-adsorbent and designated as DSSC P4. The solar cell converts light-to-electricity at an efficiency of 0.31%. This is 29% enhancement in efficiency for the DSSC without addition of CDCA in the saffron-ethanol solution. The DSSC exhibits current density at short-circuit (J _sc ) of 1.26 mA cm^?2, voltage at open circuit (V _oc ) of 0.48 V and 51% fill factor. DSSC P4 also exhibits the highest incident photon-to-current density of more than 40% at 340 nm wavelength.     

Crystallization kinetics study of cerium titanate CeTi2O6

Cerium titanate CeTi₂O₆ has been investigated recently for its photocatalytic activity and as a safe analogue to actinide-containing brannerite-like titanates (UTi₂O₆, PuTi₂O₆, e.g.) which are intensively studied because of their use for storing nuclear waste. In this paper we report on the monoclinic phase CeTi₂O₆ obtained from the Ti–Ce oxide mixture prepared by a reverse micelles directed sol–gel method and subsequently annealed. The kinetics of the isothermal crystallization process is investigated by means of Johnson–Mehl–Avrami–Kolmogorov equation. The effective activation energy of the formation of CeTi₂O₆ particles, which is an important parameter for its synthesis, is estimated.     

Off-resonance correction using an estimated linear time map

Images acquired in the presence of magnetic field deviations and reconstructed without taking into account the off-resonance, are distorted and corrupted with artifacts. Several post-processing algorithms have been developed for correcting the distortion when it is not possible to fix the field inhomogeneities. These off-resonance correction methods are, in general, slow and computing intensive. To make them faster they are usually adapted to a particular situation or approximated. One of these approximations is to assume that the field map is linear. Although this assumption makes the algorithm fast and robust it is not well suited for arbitrary field maps. On the other hand, there are k-space trajectories with an almost linear time map (time at which each k-space value is acquired), such as 2DFT and EPI. This paper presents an algorithm for off-resonance correction based on a linear time map approximation. This approximation allows a fast algorithm that takes advantage of the almost linearity of the time map and uses the whole field map to correct the images. The proposed correction algorithm reduces the off-resonance induced artifacts while being fast. The linear approximation of the time map needs to be done only once for each trajectory because it does not depend on the acquired image or field map data. The method can also be extended to a multi-plane approximation for sequences with more complex time maps.     

Thermal Degradation of Polysiloxane Coatings on E-Glass Fiber. A FTIR Study

Fourier Transform Infrared Spectroscopy and Thermal Analysis have been used to study the thermal and termooxidative degradation of polysiloxane coatings obtained by treating E-glass fiber with aqueous solutions of 3-chloropropyltriethoxysilane. Initial weight losses were due to polymerization of the coatings. Severe oxidative degradations were observed at temperatures above 180°C. At 550°C the residue of the coating was found to be silica with free silanol groups.     

Spectrofluorimetric Determination Of Indium with 1,2,4-Trihydroxyanthraquinone

A new method for the spectrofluorimetric determination of indium by formation of a fluorescent 1:1 complex with 1,2,4-trihydroxyanthraquinone is proposed. The complex is formed in a mixed, 60:40 v/v acetone-water medium at pH 3.8 provided by an acetic acid-sodium acetate buffer. The calibration graph is linear between 10 and 600 ng/ml. The effect of potential interferents on the determination was assessed and the proposed method was applied to the determination of indium in synthetic samples.     

Statistical Mechanics of a Simplified Bipartite Matching Problem: An Analytical Treatment

We perform an analytical study of a simplified bipartite matching problem in which there exists a constant matching energy, and both heterosexual and homosexual pairings are allowed. We obtain the partition function in a closed analytical form and we calculate the corresponding thermodynamic functions of this model. We conclude that the model is favored at high temperatures, for which the probabilities of heterosexual and homosexual pairs tend to become equal. In the limits of low and high temperatures, the system is extensive, however this property is lost in the general case. There exists a relation between the matching energies for which the system becomes more stable under external (thermal) perturbations. As the difference of energies between the two possible matches increases the system becomes more ordered, while the maximum of entropy is achieved when these energies are equal. In this limit, there is a first order phase transition between two phases with constant entropy.     

Optimized K-means (OKM) clustering algorithm for image segmentation

This paper presents the optimized K-means (OKM) algorithm that can homogenously segment an image into regions of interest with the capability of avoiding the dead centre and trapped centre at local minima phenomena. Despite the fact that the previous improvements of the conventional K-means (KM) algorithm could significantly reduce or avoid the former problem, the latter problem could only be avoided by those algorithms, if an appropriate initial value is assigned to all clusters. In this study the modification on the hard membership concept as employed by the conventional KM algorithm is considered. As the process of a pixel is assigned to its associate cluster, if the pixel has equal distance to two or more adjacent cluster centres, the pixel will be assigned to the cluster with null (e. g., no members) or to the cluster with a lower fitness value. The qualitative and quantitative analyses have been performed to investigate the robustness of the proposed algorithm. It is concluded that from the experimental results, the new approach is effective to avoid dead centre and trapped centre at local minima which leads to producing better and more homogenous segmented images.     

Locally adaptive bilateral clustering for universal image denoising

This paper presents a novel and efficient locally adaptive denoising method based on clustering of pixels into regions of similar geometric and radiometric structures. Clustering is performed by adaptively segmenting pixels in the local kernel based on their augmented variational series. Then, noise pixels are restored by selectively considering the radiometric and spatial properties of every pixel in the formed clusters. The proposed method is exceedingly robust in conveying reliable local structural information even in the presence of noise. As a result, the proposed method substantially outperforms other state-of-the-art methods in terms of image restoration and computational cost. We support our claims with ample simulated and real data experiments. The relatively fast runtime from extensive simulations also suggests that the proposed method is suitable for a variety of image-based products ?? either embedded in image capturing devices or applied as image enhancement software.     

Hybrid GR-SVM for prediction of surface roughness in abrasive water jet machining

This paper presents a hybridization model of support vector machine (SVM) and grey relational analysis (GRA) in predicting surface roughness value of abrasive water jet (AWJ) machining process. The influential factors of five process parameters in AWJ, namely traverse speed, water jet pressure, standoff distance, abrasive grit size and abrasive flow rate, need to be analyzed using GRA approach. Then, the irrelevance factors of process parameters are eliminated. There is a need of determining the influential factors of process parameters to the surface roughness as to develop a robust prediction model. GRA acts as feature selection method in preprocessing process of hybrid grey relational-support vector machine (GR-SVM) prediction model. Efficiency of the proposed model is demonstrated. GR-SVM presents more accurate result than conventional SVM as it removes the redundant features and irrelevant element from the experimental datasets.     

An SQP method for mathematical programs with vanishing constraints with strong convergence properties

We propose an SQP algorithm for mathematical programs with vanishing constraints which solves at each iteration a quadratic program with linear vanishing constraints. The algorithm is based on the newly developed concept of \({\mathcal {Q}}\)-stationarity (Benko and Gfrerer in Optimization 66(1):61–92, 2017). We demonstrate how \({\mathcal {Q}}_M\)-stationary solutions of the quadratic program can be obtained. We show that all limit points of the sequence of iterates generated by the basic SQP method are at least M-stationary and by some extension of the method we also guarantee the stronger property of \({\mathcal {Q}}_M\)-stationarity of the limit points.