Mass transfer in polycrystalline ytterbium monosilicate under oxygen potential gradients at high temperatures

Mass transfer in polycrystalline Yb₂SiO₅ wafers with precise composition control was evaluated and analyzed by oxygen permeation experiments at high temperatures using an oxygen tracer. Oxygen permeation proceeded due to mutual grain boundary diffusion of oxide ions and Yb ions without synergistic effects such as acceleration or suppression. The oxygen shielding properties of Yb₂SiO₅ were compared with those of the other line compounds such as Yb₂Si₂O₇ and Al₂O₃ based on the determined mass transfer parameters. It was found that the more preferentially an oxide ion diffuses in the grain boundary compared to the interior of the grain, the greater the effect of suppressing the movement of the oxide ion by applying an oxygen potential gradient becomes.     

Design of energy‐efficient train speed profiles considering fixed‐block signaling system

In dense traffic railway networks, trains may often slow down or stop between stations owing to previous train delays. If preceding train trajectory can be predicted, energy‐efficient driving can be achieved by suppressing unnecessary speed changes. In this paper, we propose an algorithm to find energy‐efficient driving considering fixed‐block signaling (FBS) system by using dynamic programming (DP). DP is suitable for use because it can optimize the control inputs with discrete and state constraints. In this paper, we discuss energy‐efficient driving by considering a FBS system using some case studies of simulation. In the simulation, we examine a technique to drive an express train in an energy‐efficient way when the preceding local train is running toward the station with passing loops. The results show that the proposed method can derive complex speed profiles for energy‐efficient driving and the train can be operated with a maximum reduced energy consumption of 8.3%.     

Systematic packaging design tools integrating functional and environmental consequences on product life cycle: Case studies on laundry detergent and milk

This study presents systematic packaging design tools integrating functional and environmental consequences on product life cycle. To design packaging for sustainability, the trade-offs between functional and environmental aspects of packaging throughout the product life cycle should be considered. However, it is difficult for packaging designers to understand the overall trade-offs because the extent of the design consequences on the entire life cycle of packaging and its contents is unclear. We developed two tools for packaging design: the Life Cycle Association Matrix (LCAM) and the Function Network Diagram (FND). The following three steps, based on literature reviews and interviews with industrial experts, were applied. Firstly, we listed the product functions and design variables related to the functions as the attributes allocated to the product life cycle. Secondly, the attributes were connected appropriately based on causal relationships. Lastly, we identified the factors to support decision making in the packaging design procedure. As a result, the LCAM depicts the design consequences on the life cycle, and the FND determines the stakeholders affected by the design consequences. Two case studies were demonstrated to analyze the trade-offs by using our tools. In the case studies, a liquid laundry detergent bottle and a milk carton were redesigned. The tools identified the design consequences and stakeholders affected by the redesign of the usability and protective function for the detergent and milk cases, respectively. The results showed the significance of understanding the design consequences on the product life cycle by integrating the functional and environmental aspects.     

Study of Cuprate Superconductivity Using the Particle Number Conserving Bogoliubov-de Gennes Equations: ARPES and STS Images From Surface Plus Bulk Layers Model

Journal of Superconductivity and Novel Magnetism - We theoretically study the superconductivity in hole-doped cuprate superconductors by employing a model composed of surface and bulk CuO $$_2$$...     

Quantitative Elemental Analysis of a Single Cell by Using Inductively Coupled Plasma-Mass Spectrometry in Fast Time-Resolved Analysis Mode

The elemental composition of a single yeast, green alga, or red blood cell (RBC) was precisely determined by using inductively coupled plasma-mass spectrometry (ICP-MS) operating in fast time-resolved analysis (TRA) mode. The technique is known as single-cell (SC)-ICP-MS. Phosphorus, sulfur, magnesium, zinc, and iron were detected in the three types of cell. The elemental composition of yeast and green alga obtained by SC-ICP-MS was consistent with results obtained from conventional ICP-MS measurements following acid digestion of the cells. Slight differences were found in the measured values between SC-ICP-MS and the conventional ICP-MS results for RBC. However, the SC-ICP-MS results for S and Fe in RBC were closer to the estimated values for these elements that were calculated from the level of hemoglobin in RBCs. The data suggest that SC-ICP-MS is suitable for the analysis of various cell types, namely, fungus, plant, and animal cells.     

Application of multiple sensory evaluations to produce fermented beverages made from sole whey using Kluyveromyces marxianus

Various fermented whey-based beverages have been developed to reduce waste. However, approaches to increase the preference of whey-based beverages are required because of the low sensory acceptability of whey. Here, we identified the better starting material (whey type), between raw whey (RW) and demineralised whey (DMW), and determined the optimal initial concentration using multiple sensory evaluations to develop acceptable fermented beverages made from sole whey with pure cultured Kluyveromyces marxianus (i.e. without additional ingredients and processing methods). Acceptance tests showed that fermented beverages made from DMW were superior to RW as the starting material. The amounts of ethanol produced were 5.0%, 7.6% and 9.5% v/v from the different initial DMW concentrations of 10%, 15% and 20% w/v, respectively. We observed a significant positive correlation (r_s = 0.32, P < 0.05) between the assessment attributes, strength of taste as alcohol beverage and overall acceptability, indicating that higher concentrations of DMW yielded a more desirable product.     

Ionization efficiency of evolved gas molecules from aerosol particles in a thermal desorption aerosol mass spectrometer: Laboratory experiments

Thermal desorption aerosol mass spectrometers (TDAMSs) with electron ionization are widely used for quantitative analysis of aerosol chemical composition, and the ionization efficiency of evolved gas molecules from aerosol particles is an important parameter for such analysis. We performed laboratory experiments using a custom-made TDAMS to investigate the key factors affecting ionization efficiency. Ammonium chloride (NH₄Cl) and ammonium iodide (NH₄I) were used as test compounds because their thermal decomposition products are expected to be simple (dominated by ammonia (NH₃) and hydrogen halide (HX)). The ion signals originating from NH₃ and HX were measured by altering the position of the ionizer relative to the vaporization point. The ratio of ion signal from NH₃ to that from HX increased with increasing divergence angle of evolved gas plumes, which suggests that the angular distribution of gas molecules could be an important factor affecting the ionization efficiency.

Copyright © 2018 American Association for Aerosol Research     

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.