Application of thermal ultrasound-assisted liquid–liquid micro-extraction coupled with HPLC-UV for rapid determination of synthetic phenolic antioxidants in edible oils

A simple, fast, and reliable liquid–liquid micro-extraction (LLME) method assisted by thermal ultrasound approach was developed for simultaneous determination of synthetic phenolic antioxidants (SPAs) in edible oils by high-performance liquid chromatography equipped with ultraviolet detector (HPLC-UV). The synthetic antioxidants were propyl gallate (PG), butylated hydroxyanisole (BHA), tert-butylhydroquinone (TBHQ), and butylated hydroxyltoluene (BHT). The best extraction conditions were observed were methanol/acetonitrile (1:1, v/v) as the solvent, ultrasound at 4 min, and a temperature of 40°C. The linearity of the calibration curves for the optimum conditions were R² > 0.989 for all of the SPAs in a range from 1–200 μg ml⁻¹. Relative standard deviation (RSD %) for five analysis was in range of 2.83% to 4.21%. Limit of detection (LOD) and limit of quantification (LOQ) were obtained in range of 0.012–0.06 and 0.04–0.2 μg g⁻¹, respectively. With regard to recovery, a range of 91%–116% was calculated for the spiked edible oils.     

Covalent surface functionalization of nonwoven fabrics with controlled hydrophobicity,water absorption,and pH regulation properties

A modular method for functionalization of nonwoven fabrics was developed using a two-step process. In the first step, the fabrics were grafted with a linker molecule, 10-undecenoyl chloride, via esterification, followed by attachment of a functional material under UV irradiation. Perfluorodecanethiol and 3-mercaptopropionic acid (MPA) were connected to the linker-modified fabrics using thiol-ene click chemistry. Perfluorodecanethiol modified fabrics exhibited hydrophobicity with water contact angle of about 140° while MPA-modified fabrics were able to lower the pH of a solution by about 1.6. We additionally demonstrated the possibility to connect functional polymers to the linker-modified fabrics by radical graft polymerization of acrylic acid; this produced a thin layer of the polymer on the surface of the fabric. Fabrics modified with poly(acrylic acid) exhibited increased hydrophilicity with water contact angle of 0° for both cotton and viscose-polyester fabrics, while the water absorption capability for polypropylene fabrics increased from about 50 to 1200%.     

A bio-inspired gelatin-based pH- and thermal-sensitive magnetic hydrogel for in vitro chemo/hyperthermia treatment of breast cancer cells

Gelatin (Gel)-based pH- and thermal-responsive magnetic hydrogels (MH-1 and MH-2) were designed and developed as novel drug delivery systems (DDSs) for cancer chemo/hyperthermia therapy. For this goal, Gel was functionalized with methacrylic anhydride (GelMA), and then copolymerized with (2-dimethylaminoethyl) methacrylate (DMAEMA) monomer in the presence of methacrylate-end capped magnetic nanoparticles (MNPs) as well as triethylene glycol dimethacrylate (TEGDMA; as crosslinker). Afterward, a thiol-end capped poly(N-isopropylacrylamide) (PNIPAAm-SH) was synthesized through an atom transfer radical polymerization technique, and then attached onto the hydrogel through “thiol-ene” click grafting. The preliminary performances of developed MHs for chemo/hyperthermia therapy of human breast cancer was investigated through the loading of doxorubicin hydrochloride (Dox) as an anticancer agent followed by cytotoxicity measurement of drug-loaded DDSs using MTT assay by both chemo- and chemo/hyperthermia-therapies. Owing to porous morphologies of the fabricated magnetic hydrogels according to scanning electron microscopy images and strong physicochemical interactions (e.g., hydrogen bonding) the drug loading capacities of the MH-1 and MH-2 were obtained as 72 ± 1.4 and 77 ± 1.8, respectively. The DDSs exhibited acceptable pH- and thermal-triggered drug release behaviors. The MTT assay results revealed that the combination of hyperthermia therapy and chemotherapy has synergic effect on the anticancer activities of the developed DDSs.     

A study on melt recycling of bio-based polypropylene/thermoplastic starch compound

The compulsion to use bioplastics has increased significantly today. One of the important aspects of plastics is their recyclability. Therefore, the important question of this research is that although bio-based compounds containing starch are sensitive to thermal-mechanical recycling processes, are such products thermally recyclable? To answer the question, polypropylene (PP)/thermoplastic starch (TPS) compound granules were extruded up to five times, and in the other part, single-extruded granules were blended at different ratios with virgin granules by extrusion. In order to characterize these samples, Fourier transform infrared spectroscopy, thermogravimetric analysis, differential scanning calorimetry, rotational disc rheometry, tensile properties, and appearance evaluation were used. The results showed that it is possible to recycle PP/TPS granules up to four times repetition of the extrusion operation and the fifth repetition also showed slight changes. There was also a blend of single-extruded granules with virgin material up to a 50:50% composition without significant variation.     

Robust face recognition against expressions and partial occlusions

Facial features under variant-expressions and partial occlusions could have degrading effect on overall face recognition performance. As a solution, we suggest that the contribution of these features on final classification should be determined. In order to represent facial features contribution according to their variations, we propose a feature selection process that describes facial features as local independent component analysis(ICA) features. These local features are acquired using locally lateral subspace(LLS) strategy.Then, through linear discriminant analysis(LDA) we investigate the intraclass and interclass representation of each local ICA feature and express each feature s contribution via a weighting process. Using these weights, we define the contribution of each feature at local classifier level. In order to recognize faces under single sample constraint, we implement LLS strategy on locally linear embedding(LLE) along with the proposed feature selection. Additionally, we highlight the efficiency of the implementation of LLS strategy. The overall accuracy achieved by our approach on datasets with different facial expressions and partial occlusions such as AR, JAFFE,FERET and CK+ is 90.70%. We present together in this paper survey results on face recognition performance and physiological feature selection performed by human subjects.     

Coordinated design of TCSC and PSS controllers using VURPSO and Genetic algorithms for multi-machine power system stability

Thyristor controlled series capacitor (TCSC) can regulate line impedance and therefore increase transferred power of the system. On the other hand power system stabilizer (PSS) increases dynamic stability of generator. To enhance the stability, combination of TCSC and PSS can be applied, and in such a case coordination of TCSC and PSS is essential. This paper applies this combined controller in order to enhance the stability of multi-machine system. Parameters of these controllers are optimized by velocity update relaxation particle swarm optimization (VURPSO) algorithm and Genetic algorithm (GA). The simulation results show that the combination of VURPSO algorithm and GA leads to a better design and stability.     

Fast implementation of dense stereo vision algorithms on a highly parallel SIMD architecture

In this paper, we present faster than real-time implementation of a class of dense stereo vision algorithms on a low-power massively parallel SIMD architecture, the CSX700. With two cores, each with 96 Processing Elements, this SIMD architecture provides a peak computation power of 96 GFLOPS while consuming only 9 Watts, making it an excellent candidate for embedded computing applications. Exploiting full features of this architecture, we have developed schemes for an efficient parallel implementation with minimum of overhead. For the sum of squared differences (SSD) algorithm and for VGA (640 × 480) images with disparity ranges of 16 and 32, we achieve a performance of 179 and 94 frames per second (fps), respectively. For the HDTV (1,280 × 720) images with disparity ranges of 16 and 32, we achieve a performance of 67 and 35 fps, respectively. We have also implemented more accurate, and hence more computationally expensive variants of the SSD, and for most cases, particularly for VGA images, we have achieved faster than real-time performance. Our results clearly demonstrate that, by developing careful parallelization schemes, the CSX architecture can provide excellent performance and flexibility for various embedded vision applications.     

A Model for Locating Park-and-Ride Facilities on Urban Networks Based on Maximizing Flow Capture: A Case Study of Isfahan, Iran

Traffic congestion is one of the main problems in large cities for which several approaches have been proposed. Park-and-ride is one of the best approaches that can remove traffic from the traffic network. Park-and-ride facilities are an important part of urban mass transit systems, effectively extending the service area and attracting commuters and other people who may not otherwise have used mass transit. However, its efficiency depends on its location in the urban network. In this research, we focus on travel time of shortest paths instead of the distance criterion for computing network traffic and develop a model for finding the best location(s) for siting park-and-ride systems so as to minimize the network traffic. The model is formulated based on population points, potential sites for park-and-ride establishment, and several Central Business District (CBDs). Then we present a Genetic algorithm that has been proved to be efficient in solving large size problems. Finally, the proposed model is used to locate park-and-ride facilities in the city of Isfahan, Iran.