Fumaric acid in apple juice: a potential indicator of microbial spoilage of apples used as raw material.

The effects of heat treatment (evaporation and excessive heating), and microbial contamination (Rhizopus stolonifer, Penicillium expansum and Lactobacillus plantarum) as sources of fumaric acid formation in apple juice concentrates were investigated. Fumaric acid formed in apple juice did not exceed 1.0 mg l(-1) during both commercial-scale evaporation and laboratory-scale excessive heat treatment, indicating that malic dehydration is not the primary source of fumaric acid formation. However, R. stolonifer and L. plantarum produced 18.23 +/- 0.82 and 5.39 +/- 0.31 mg l(-1) fumaric acid as determined in the raw juice obtained from contaminated apples after 5 days of incubation. The mean fumaric acid content of apple juice concentrates manufactured in 2000, 2001 and 2002 were determined as 4.9 +/- 1.9, 5.7 +/- 2.8 and 4.1 +/- 2.6 mg l(-1), respectively. The overall results suggest that the primary source of fumaric acid in apple juice concentrate is the use of apples decayed by certain microorganisms capable of producing fumaric acid.     

The effect of using an exopolysaccharide‐producing culture on the physicochemical properties of low‐fat and reduced‐fat Kasar cheeses

A mixed starter culture containing exopolysaccharide (EPS)‐producing strains of Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus was combined with Lactobacillus helveticus LH301 and used in the manufacture of low‐fat and reduced‐fat Kasar cheeses. For comparison, low‐fat (C10) and reduced‐fat (C20) cheeses were made using EPS‐producing (EPS⁺) starter strain and EPS‐non‐producing (EPS^?) starter strain. The physicochemical properties of the cheeses were assessed in terms of chemical composition, texture, microstructure and microbial content over 90 days. Cheeses made with EPS‐producing culture (EPS10 and EPS20) had lower protein contents than control cheeses with 10% and 20% fat in dry basis (C10 and C20). Scanning electron microscopy images showed that using EPS‐producing culture resulted in a less compact protein matrix and sponge‐like structure in the cheese samples. In general, cheeses made using EPS‐producing culture had lower total viable counts. This could be related to the reduced survivability of EPS‐producing cells in the cheese matrix during ripening due to autolysis ability.     

Yarn twist measurement using digital imaging

Digital image analysis techniques in the spatial and frequency domains for twist measurement of yarns are described. A spatial technique is developed to extract the twist angle through the analysis of the yarn core image. Then, a Fourier transformation technique is applied to yarn images to measure the orientation of the fibre on the yarn surface. Finally, a hybrid method that incorporates frequency domain filtering prior to spatial analysis is proposed. The trials show that spatial analysis is a fast method and can successfully predict the twist in the yarn. Fourier transformation technique is quite sensitive to the protruding fibres obstructing the yarn surface, which may result in measurements having high variations. For yarns having little amount of hairs protruding from the core, the results agreed reasonably well with actual twist levels. Frequency domain filtering in conjunction with the spatial analysis of the yarn surface is found to be superior in terms of accuracy. The twist values calculated using the more reliable diameter measurements with back-lit images together with twist angles from the front-lit images are found to be more accurate when compared with the actual values.     

Automatic detection of building roofs from point clouds produced by the dense image matching technique

Three-dimensional (3D) spatial information of object points is a vital requirement for many disciplines. Laser scanning technology and techniques based on image matching have been used extensively to produce 3D dense point clouds. These data are used frequently in various applications, such as the generation of digital surface model (DSM)/digital terrain model (DTM), extracting objects (e.g., buildings, trees, and roads), 3D modelling, and detecting changes. The aim of this study was to extract the building roof points automatically from the 3D point cloud data created via the image matching techniques with optical aerial images (with red, green, and blue band (RGB) and infrared (IR)). In the first stage of the study, as an alternative to laser scanning technology, which is more expensive than optical imaging systems, the 3D point clouds were produced by matching high-resolution images using a Semi Global Matching algorithm. The normalized difference vegetation index (NDVI) values for each point were calculated using the spectral information (RGB + IR) in the 3D point cloud data, and the points that represented the vegetation cover were determined using these values. In the second stage, existing ground and non-ground points that were free of vegetation cover were determined within the point cloud. Subsequently, only the points on the roof of the building were detected automatically using the proposed algorithm. Thus, points of the roofs of buildings located in areas with different topographic characteristics were detected automatically detected using only images. It was determined that the average values of correctness (Corr), completeness (Comp), and quality (Q) of the pixel-based accuracy analysis metrics were 95%, 98%, and 93%, respectively, in the selected test areas. According to the results of the accuracy analysis, it is clear that the proposed algorithm is very successful in automatic extraction of building roof points.     

Adaptive architectures for control of uncertain dynamical systems with actuator and unmodeled dynamics

In adaptive control of uncertain dynamical systems, it is well known that the presence of actuator and/or unmodeled dynamics in feedback loops can yield to unstable closed‐loop system trajectories. Motivated by this standpoint, this paper focuses on the analysis and synthesis of multiple adaptive architectures for control of uncertain dynamical systems with both actuator and unmodeled dynamics. Specifically, we first analyze model reference adaptive control architectures with standard, hedging‐based, and expanded reference models for this class of uncertain dynamical systems and develop sufficient stability conditions. We then synthesize a robustifying term for the latter architecture and analytically show that this term can allow for a relaxed sufficient stability condition. The proposed theoretical treatments involve Lyapunov stability theory, linear matrix inequalities, and matrix mathematics. Finally, we compare the resulting sufficient stability conditions of the considered adaptive control architectures on a benchmark mechanical system subject to actuator and unmodeled dynamics.     

Tunable Fano-Resonant Metasurfaces on a Disposable Plastic-Template for Multimodal and Multiplex Biosensing

Metasurfaces are engineered nanostructured interfaces that extend the photonic behavior of natural materials, and they spur many breakthroughs in multiple fields, including quantum optics, optoelectronics, and biosensing. Recent advances in metasurface nanofabrication enable precise manipulation of light–matter interactions at subwavelength scales. However, current fabrication methods are costly and time-consuming and have a small active area with low reproducibility due to limitations in lithography, where sensing nanosized rare biotargets requires a wide active surface area for efficient binding and detection. Here, a plastic-templated tunable metasurface with a large active area and periodic metal–dielectric layers to excite plasmonic Fano resonance transitions providing multimodal and multiplex sensing of small biotargets, such as proteins and viruses, is introduced. The tunable Fano resonance feature of the metasurface is enabled via chemical etching steps to manage nanoperiodicity of the plastic template decorated with plasmonic layers and surrounding dielectric medium. This metasurface integrated with microfluidics further enhances the light–matter interactions over a wide sensing area, extending data collection from 3D to 4D by tracking real-time biomolecular binding events. Overall, this work resolves cost- and complexity-related large-scale fabrication challenges and improves multilayer sensitivity of detection in biosensing applications.     

Equilibrium and kinetic mechanism for Reactive Black 5 sorption onto high lime Soma fly ash

Batch adsorption studies were carried out for the sorption of C.I. Reactive Black 5, a reactive dye, onto high lime fly ash, obtained from Soma Thermal Power Plant (Turkey), to be low cost adsorbent. The effect of various experimental parameters such as contact time, adsorbent dose and initial dye concentration were investigated. Determination of the adsorption equilibrium concentrations was determined by UV-vis spectrophotometry analytical method. Equilibrium data were fitted to the Freundlich and Langmuir isotherm equations and the equilibrium data were found to be well represented by the Freundlich isotherm equation. The adsorption kinetics of C.I. Reactive Black 5 onto high lime fly ash were also studied to characterize of the surface complexation reaction. A pseudo-second-order mechanism has been developed to predict the rate constant of the adsorption, the equilibrium capacity and initial adsorption rate with the effect of initial concentration. A single-stage batch adsorber design of the adsorption of C.I. Reactive Black 5 onto high lime fly ash has been studied based on the Freundlich isotherm equation.     

An experimental evaluation of visual similarity for HDR images

In this paper, we investigate visual similarity for high dynamic range (HDR) images. We collect crowdsourcing data through a web-based experimental interface, in which the participants are asked to choose one of the two candidate images as being more similar to the query image. Triplets forming the query-and-candidates sets are obtained by random sampling from existing HDR data sets. Experimental control factors include choice of tone mapping operator (TMO), choice of distance metric, and choice of image feature. The image features that we experiment with are chosen from the features that are commonly used in the usual low dynamic range setting including features learned via Convolutional Neural Networks. The set of image features also includes combined features where the combination coefficients are estimated using logistic regression. We compute correlations between human judgments and quantitative features to understand how much each feature contributes to visual similarity. Combined features yield nearly 84% agreement with human judgments when applied on tone mapped images. Though we observed that using common features directly on raw or linearly scaled HDR images yield subpar correlation estimates compared to using them on tone mapped HDR images, we did not observe significant effect due to the choice of TMO on the estimates. As an application, we propose an improvement to style-based tone mapping for more correctly imparting desired styles to HDR images with different characteristics.

     

Use of ultrasonic energy in reactive dyeing of cellulosic fabrics

The use of ultrasonic energy in dyeing cotton fabrics with monochlorotriazine and vinylsulphone reactive dyes has been studied spectrophotometrically. The dyeings carried out conventionally and by the use of ultrasonic techniques were compared in terms of percentage exhaustion, total amount of dye transferred to the washing bath after dyeing, fastness properties and colour values of the dyed materials. Overall results have shown that the use of ultrasound in reactive dyeing of cellulosic fabrics can result in energy savings, less water consumption, increased depth of colour and better process conditions.