Thermal oxidation of vanillin affects its antioxidant and antimicrobial properties

Accelerated oxidation of vanillin was studied by isothermal and non-isothermal differential scanning calorimetry (DSC) in model solutions. Exothermic peaks of DSC thermograms, due to the oxidation of vanillin, were observed. Vanillin oxidation to vanillic acid was confirmed by the detection of vanillic acid in heated vanillin samples using GC–MS. The effect of temperature on vanillin oxidation was studied by conducting DSC experiments with pure vanillin at several different final temperatures and by subsequent determination of vanillin and vanillic acid by GC–MS.     

Incremental refinement of image salient-point detection

Low-level image analysis systems typically detect "points of interest", i.e., areas of natural images that contain corners or edges. Most of the robust and computationally efficient detectors proposed for this task use the autocorrelation matrix of the localized image derivatives. Although the performance of such detectors and their suitability for particular applications has been studied in relevant literature, their behavior under limited input source (image) precision or limited computational or energy resources is largely unknown. All existing frameworks assume that the input image is readily available for processing and that sufficient computational and energy resources exist for the completion of the result. Nevertheless, recent advances in incremental image sensors or compressed sensing, as well as the demand for low-complexity scene analysis in sensor networks now challenge these assumptions. In this paper, we investigate an approach to compute salient points of images incrementally, i.e., the salient point detector can operate with a coarsely quantized input image representation and successively refine the result (the derived salient points) as the image precision is successively refined by the sensor. This has the advantage that the image sensing and the salient point detection can be terminated at any input image precision (e.g., bound set by the sensory equipment or by computation, or by the salient point accuracy required by the application) and the obtained salient points under this precision are readily available. We focus on the popular detector proposed by Harris and Stephens and demonstrate how such an approach can operate when the image samples are refined in a bitwise manner, i.e., the image bitplanes are received one-by-one from the image sensor. We estimate the required energy for image sensing as well as the computation required for the salient point detection based on stochastic source modeling. The computation and energy required by the proposed incremental refinement approach is compared against the conventional salient-point detector realization that operates directly on each source precision and cannot refine the result. Our experiments demonstrate the feasibility of incremental approaches for salient point detection in various classes of natural images. In addition, a first comparison between the results obtained by the intermediate detectors is presented and a novel application for adaptive low-energy image sensing based on points of saliency is presented.     

Surface modification of poly (ethylene terephthalate) fabric by soy protein isolate hydrogel for wound dressing application

In this study, a composite of poly (ethylene terephthalate) (PET) fabric and soy protein isolate (SPI) hydrogel loaded with gabapentin was developed. For covalent attachment of SPI on the surface of PET fabric, graft polymerization of acrylic acid (AA) on the surface of PET fabric was performed and then carboxyl groups available in the structure of AA were activated using EDAC and then SPI was coated on the surface of PET fabric. The results revealed appropriate connection between hydrogel and modified fabric. The hydrogel was characterized by swelling test and the drug release behavior was investigated. It was found that the casting temperature affects the swelling ratio of the hydrogel and an appropriate release profile of the drug was observed. The surface of fabric was characterized by contact angle measurement, electron microscopy, and infrared spectroscopy. In vitro cell culture study was performed using NIH 3T3 mouse fibroblasts to investigate the biocompatibility of final composite and MTS results along with morphology of cells on the surface of PET fabric coated with SPI revealed the biocompatibility of final product and no cell cytotoxicity was observed in modified PET fabric.     

Cycle time reduction by improved MRP-based production planning

The important practical problem of planning the production of large assemblies employing an MRP-based system is considered. The objective is to produce products on-time, with minimal cycle time and low work-in-process costs. The approach is based on the determination of accurate lead-time estimates and on the introduction and use of lead-time offsets in the solution methodology. An effective Lead-time Evaluation and Scheduling Algorithm (LETSA) is employed that can perform detailed backward scheduling of operations belonging to a large assembly on a given facility with an objective of minimizing the cycle time. A scaling procedure is used to account for capacity sharing effects by multiple products in a common facility. These scaled lead-time estimates are then employed by an MRP-based system to release work-orders on the shop-floor. The effectiveness of these lead-times and lead-time offsets are evaluated by simulating production using the MRP generated order release times and verifying on-time completion of the multiple assemblies in the common facility. Numerical experiments are presented to validate the performance of the approach. Optimized batch sizes for minimal work-in-process (WIP) costs can also be obtained using LETSA. Thus, the important objectives of minimizing cycle time for on-time delivery and minimizing schedule costs can be accomplished simultaneously.     

Reflective and Complementary Transmissive All-Printed Electrochromic Displays Based on Prussian Blue

By combining the electrochromic (EC) properties of Prussian blue (PB) and poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), complementary EC displays manufactured by slot-die coating and screen printing on flexible plastic substrates are reported. Various display designs have been realized, resulting in displays operating in either transmissive or reflective mode. For the transmission mode displays, the color contrast is enhanced by the complementary switching of the two EC electrodes PB and PEDOT:PSS. Both electrodes are either exhibiting a concurrent colorless or blue appearance. For the displays operating in reflection mode, a white opaque electrolyte is used in conjunction with the EC properties of PB, resulting in a display device switching between a fully white state and a blue-colored state. The developments of the different device architectures, that either operate in reflection or transmission mode, demonstrate a scalable manufacturing approach of all-printed EC displays that may be used in a large variety of Internet of Things applications.     

APPLICATION OF THE PRECONDITIONED CONJUGATE GRADIENTS METHOD IN THE SIMULATION OF RELATIVE PERMEABILITY PROPERTIES OF POROUS MEDIA

A model that is after the determination of the relative permeability characteristics of porous media is presented. It is part of a general model that deals with the simulation of capillary phenomena and immiscible fluid flow behaviour in porous media. The relative permeability characteristics in a water wet porous medium are simulated with the use of three-dimensional (3-D) network models of pore structure with pore body and pore throat size distributions. The major assumption involved is that a cubic network of pore bodies connected by pore throats with pore body and pore throat size distribution respectively, is a realistic representation of the pore structure of a porous medium. The physical laws that apply in real media are simulated in the network analysis, and the computed results are compared with experimental findings. A new algorithm was developed that leads to the solution of a large set of linear equations, with a sparse and positive definite coefficient matrix. Results obtained with the application of the Preconditioned Conjugate Gradients method and numerical aspects of the simulation are presented and discussed. Comparison of this method with other available numerical methods is also made. It is concluded that the Preconditioned Conjugate Gradients method is advantageous for large networks with regards to time of solution, convergence, and accuracy. The validity of the algorithm is tested against other methods in the literature.