Structural modifications of sugar beet pectin and the relationship of structure to functionality

The emulsifying properties of sugar beet pectin (SBP) were investigated in relation to its molecular structure. SBP has been subjected to an enhancement process, and this material was here compared with conventional non-enhanced SBP. The oil-in-water emulsification properties of both were compared at 1.5% concentration at pH 3.25, using 15% middle-chain triglyceride as the oil phase. Their emulsification behavior after various enzyme treatments decreased in the order: protease > arabinanase/galactanase mixture > polygalacturonase. The enzyme treatment also decreased the molecular weight of SBP. Protease degraded the high molecular weight carbohydrate–protein complex. Arabinanase/galactanase mixture was more effective in decreasing the emulsification performance than polygalacturonase. The results confirm the key role of protein as the anchor for the oil droplets and identify also the contribution of the neutral lateral chains in stabilizing emulsions by forming a hydrated layer. Protein also aggregates, which functions as a linker for the association of the carbohydrate chains consequent to the enhancement process.     

Swallowing profiles of food polysaccharide gels in relation to bolus rheology

Swallowing profiles of food polysaccharide gels were investigated in relation to bolus rheology. Polysaccharide gel from either gellan gum or a mixture of gellan gum and psyllium seed gum was used as a model food. Acoustic analysis and sensory evaluation were carried out to investigate the swallowing profiles using the same human subjects. Model bolus was prepared through instrumental mastication using a mechanical simulator to mimic the action of the human jaw in the presence or absence of artificial saliva and was subjected to dynamic viscoelasticity measurements to investigate the rheological properties. Bolus from the binary gel was shorter in time required to transfer through the pharyngeal phase due to mass flow and was scored higher in sensory perceived cohesiveness (bolus forming) than that from gellan gum gel. Model bolus from the binary gel showed a rheologically weak gel (or structured fluid) behavior and was higher in structural homogeneity than that from gellan gum gel. Also, dynamic viscoelasticity parameters of the binary gel were less dependent on the addition level of saliva. Results indicate that the viscoelasticity balance is a key for texture design of dysphagia foods in relation to the saliva miscibility.     

Note: Low temperature superconductor superconducting quantum interference device system with wide pickup coil for detecting small metallic particles

A one-channel low temperature superconductor superconducting quantum interference device system comprising a second-order axial gradiometer with a sensing area of 10 mm × 190 mm was developed. The gradiometer was mounted in a liquid-helium dewar (450-mm diameter; 975-mm length), with a gap of 12 mm between the pickup coil and the dewar-tail surface. The magnetic field sensitivity was measured to be 16 fT∕Hz(1∕2) in the white noise regime above 2 Hz. The system was used to measure stainless steel particles of different sizes passing through the sensing area. A 100-μm diameter SUS304 particle was readily detected passing at different positions underneath the large pickup coil by measuring its 1.3-pT magnetic field. Thus, the system was shown to be applicable to quality control of lamination sheet products such as lithium ion batteries.     

Deep multi-layered GMDH-type neural network using revised heuristic self-organization and its application to medical image diagnosis of liver cancer

In this study, the deep multi-layered group method of data handling (GMDH)-type neural network algorithm using revised heuristic self-organization method is proposed and applied to medical image diagnosis of liver cancer. The deep GMDH-type neural network can automatically organize the deep neural network architecture which has many hidden layers. The structural parameters such as the number of hidden layers, the number of neurons in hidden layers and useful input variables are automatically selected to minimize prediction error criterion defined as Akaike’s information criterion (AIC) or prediction sum of squares (PSS). The architecture of the deep neural network is automatically organized using the revised heuristic self-organization method which is a type of the evolutionary computation. This new neural network algorithm is applied to the medical image diagnosis of the liver cancer and the recognition results are compared with the conventional 3-layered sigmoid function neural network.     

Deep feedback GMDH-type neural network and its application to medical image analysis of MRI brain images

The deep feedback group method of data handling (GMDH)-type neural network is applied to the medical image analysis of MRI brain images. In this algorithm, the complexity of the neural network is increased gradually using the feedback loop calculations. The deep neural network architecture is automatically organized so as to fit the complexity of the medical images using the prediction error criterion defined as Akaike’s information criterion (AIC) or prediction sum of squares (PSS). The recognition results show that the deep feedback GMDH-type neural network algorithm is useful for the medical image analysis of MRI brain images, because the optimum neural network architectures fitting the complexity of the medical images are automatically organized so as to minimize the prediction error criterion defined as AIC or PSS.     

Medical image analysis of abdominal X-ray CT images by deep multi-layered GMDH-type neural network

In this study, a deep multi-layered group method of data handling (GMDH)-type neural network is applied to the medical image analysis of the abdominal X-ray computed tomography (CT) images. The deep neural network architecture which has many hidden layers are automatically organized using the deep multi-layered GMDH-type neural network algorithm so as to minimize the prediction error criterion defined as Akaike’s information criterion (AIC) or prediction sum of squares (PSS). The characteristics of the medical images are very complex and therefore the deep neural network architecture is very useful for the medical image diagnosis and medical image recognition. In this study, it is shown that this deep multi-layered GMDH-type neural network is useful for the medical image analysis of abdominal X-ray CT images.     

Near lossless coding of sparse histogram images based on zero-skip quantization

Multimedia Tools and Applications - This paper introduces a zero-skip quantization (ZS.Q) scheme for the near lossless coding of sparse histogram images. Increases in the range of pixel values and...     

Compositional and structural dependence of up-converting rare earth fluorides obtained through EDTA assisted hydro/solvothermal synthesis

In this feature article, we highlight our works on compositional and structural dependence of up-converting rare earth (RE) fluorides obtained through ethylenediamine tetraacetic acid (EDTA) assisted hydrothermal synthesis. Various nanostructures were obtained by tuning of experimental conditions, such as precursor’s concentration, degree of doping, reaction time and solvent used during synthesis. We correlated in detail the structural, morphological and optical properties of YF₃ and NaYF₄ compounds co-doped with Yb³⁺ and Er³⁺ (introduced in total mol% of 8 and 20). For this purpose, X-ray powder diffraction, scanning and transmission electron microscopy, energy dispersive X-ray and Furrier transform infrared spectroscopy, as well as, the photoluminescence spectra and decay times were recorded and analyzed. The particle size and phase content were found to be dependent on the nucleation rate, which, in turn, was governed by the precursor concentration, degree of doping and solvent type. The transformation from cubic to hexagonal NaYF₄:Yb³⁺/Er³⁺ phase was found to be sensitive to the reaction time and precursors concentration, while the crystallization of orthorhombic YF₃:Yb³⁺/Er³⁺ phase is achieved through lowering of dopants concentration or by changing of solvent during hydrothermal treatment. The up-conversion photoluminescence demonstrated morphology and crystal phase dependence and is found to be superior in microcrystalline samples, independent on their phase composition.     

Minimal effective dose on serum cholesterol concentration and the safety evaluation of dressing containing plant sterol in Japanese subjects

We examined the minimal effective dose on serum cholesterol concentration and the safety of dressing containing plant sterol in humans. EXP.1: Sixty-eight healthy Japanese males (total cholesterol (TC) > or = 170 mg/dL) were randomly divided into four groups, and were given 0, 400, 800 or 1200 mg/day of plant sterol in 15 g dressing for 4 weeks followed by the washout period of 4 weeks. Although there were no significant differences in serum TC and low-density lipoprotein cholesterol (LDL-C) concentrations among all groups after feeding plant sterol for 4 weeks, in 36 subjects with TC > or = 220 mg/dL, serum LDL-C concentration tended to reduce when received 800 or 1200 mg of plant sterol, and the difference between 0 and 1200 mg groups was statistically significant. The difference between 0 and 800 mg groups was near significant (p=0.053). Intake of 400 mg of plant sterol did not change serum LDL-C concentration. EXP.2: Twenty-one healthy Japanese subjects (TC > or = 180 mg/dL, 10 men, 11 women) were given 2400 mg/day of plant sterol in 45 g dressing for 4 weeks. Clinical data were all remained normal. These results indicated that minimal effective dose of the plant sterol on serum cholesterol concentration in healthy male subjects is around 800 mg/day, and intake of 2400 mg/day of plant sterol is regarded to be safe.