Structural Investigation of a Rapidly Quenched 20Li4SiO4·80Li2WO4 Glass

A 20Li₄SiO₄·80Li₂WO₄ glass was prepared by the rapid quenching technique, and its structure was investigated by X-ray diffraction (XRD) and Raman scattering. The coordination number of the oxygen atoms around a tungsten atom, N_O/W, was determined to be 4.8 by XRD and 4.6 by Raman scattering. The deviation of N_O/W from 4 resulted from the coexistence of condensed structural units, such as WO₆, Si₂O⁶⁻₇ ions containing bridging oxygens, WO²⁻₄ ions, and SiO⁴⁻₄ ions.     

Laser-Sintered Barium Titanate

Laser sintering of alkoxy-derived ultrafine BaTiO₃ powders was investigated. The temperature increases of the sample with laser irradiation were measured with a thermocouple. It was found that laser irradiation could generate enough heat to sinter ceramics. A slurry was prepared by mixing an alkoxy-derived BaTiO₃ powder, binder additives, solvent, and plasticizer. The slurry was tape cast and dried to give a green sheet. The green sheet was laser sintered and was then characterized by SEM, XRD, and density measurements. The effect of burnout before laser irradiation and the characteristic microstructure of laser-sintered BaTiO₃ are described.     

A near-infrared study of thermally induced structural changes in polyethylene crystal

Thermally induced structural changes of polyethylene (PE) have been studied by means of near-infrared (NIR) spectroscopy in the course of heating up to the melting temperature. NIR bands characteristic of the regular orthorhombic phase, the conformationally disordered hexagonal phase, and the amorphous phase have been successfully identified. It has been found that for the unoriented PE sample, the disordering process of orthorhombic lattice starts above room temperature and that it mostly occurs above 100 °C for the uniaxially oriented PE sample. In the latter case, the enhancement of crystallinity has clearly been detected just below T_m due to the reorganization of crystalline lattice. For the geometrically constrained ultradrawn PE sample, the phase transition from orthorhombic to hexagonal phase has been detected immediately below the melting point. The NIR bands characteristic of the hexagonal phase have been confirmed definitely. Usefulness of NIR spectroscopy has been demonstrated successfully in such a study of thermally induced phase transition behavior of PE samples with appreciable thickness, for which mid-IR spectroscopy is difficult to apply because of the intensity saturation of various key bands.     

Multi-objective genetic algorithm-based sample selection for partial least squares model building with applications to near-infrared spectroscopic data

In this study, multi-objective genetic algorithms (GAs) are introduced to partial least squares (PLS) model building. This method aims to improve the performance and robustness of the PLS model by removing samples with systematic errors, including outliers, from the original data. Multi-objective GA optimizes the combination of these samples to be removed. Training and validation sets were used to reduce the undesirable effects of over-fitting on the training set by multi-objective GA. The reduction of the over-fitting leads to accurate and robust PLS models. To clearly visualize the factors of the systematic errors, an index defined with the original PLS model and a specific Pareto-optimal solution is also introduced. This method is applied to three kinds of near-infrared (NIR) spectra to build PLS models. The results demonstrate that multi-objective GA significantly improves the performance of the PLS models. They also show that the sample selection by multi-objective GA enhances the ability of the PLS models to detect samples with systematic errors.     

New methodology to obtain a calibration model for noninvasive near-infrared blood glucose monitoring

This paper reports new methodology to obtain a calibration model for noninvasive blood glucose monitoring using diffuse reflectance near-infrared (NIR) spectroscopy. Conventional studies of noninvasive blood glucose monitoring with NIR spectroscopy use a calibration model developed by in vivo experimental data sets. In order to create a calibration model, we have used a numerical simulation of light propagation in skin tissue to obtain simulated NIR diffuse reflectance spectra. The numerical simulation method enables us to design parameters affecting the prediction of blood glucose levels and their variation ranges for a data set to create a calibration model using multivariate analysis without any in vivo experiments in advance. By designing the parameters and their variation ranges appropriately, we can prevent a calibration model from chance temporal correlations that are often observed in conventional studies using NIR spectroscopy. The calibration model (regression coefficient vector) obtained by the numerical simulation has a characteristic positive peak at the wavelength around 1600 nm. This characteristic feature of the regression coefficient vector is very similar to those obtained by our previous in vitro and in vivo experimental studies. This positive peak at around 1600 nm also corresponds to the characteristic absorption band of glucose. The present study has reinforced that the characteristic absorbance of glucose at around 1600 nm is useful to predict the blood glucose level by diffuse reflectance NIR spectroscopy. We have validated this new calibration methodology using in vivo experiments. As a result, we obtained a coefficient of determination, r2, of 0.87 and a standard error of prediction (SEP) of 12.3 mg/dL between the predicted blood glucose levels and the reference blood glucose levels for all the experiments we have conducted. These results of in vivo experiments indicate that if the parameters and their vibration ranges are appropriately taken into account in a numerical simulation, the new calibration methodology provides us with a very good calibration model that can predict blood glucose levels with small errors without conducting any experiments in advance to create a calibration model for each individual patient. This new calibration methodology using numerical simulation has promising potential for NIR spectroscopy, especially for noninvasive blood glucose monitoring.     

A general model-based approach to two-dimensional infrared correlation spectroscopy incorporating the global phase angle

We describe a theoretical framework for a model-based approach to two-dimensional correlation spectroscopy that is generally applicable to any arbitrary model function. The method is based on the correlation between spectral data and a set of model waveforms with a varying correlation index, the global phase angle Theta. When experimental spectral intensity variations are expressed as sinusoidal, exponential, Lorentzian, or quadratic functions, the proposed approach allows us to estimate the quantitative values of the target parameters in those expressions. In addition, this method enables us to assess the sequential order in a series of bands undergoing non-identical intensity changes in a dynamic data set. We present both simulated and experimentally obtained data that illustrate that the deviations from linearity of the absorption band intensity waveforms are clearly detected and can be quantitatively estimated using quadratic functions.     

Noninvasive near-infrared blood glucose monitoring using a calibration model built by a numerical simulation method: Trial application to patients in an intensive care unit

We have applied a new methodology for noninvasive continuous blood glucose monitoring, proposed in our previous paper, to patients in ICU (intensive care unit), where strict controls of blood glucose levels are required. The new methodology can build calibration models essentially from numerical simulation, while the conventional methodology requires pre-experiments such as sugar tolerance tests, which are impossible to perform on ICU patients in most cases. The in vivo experiments in this study consisted of two stages, the first stage conducted on healthy subjects as preliminary experiments, and the second stage on ICU patients. The prediction performance of the first stage was obtained as a correlation coefficient (r) of 0.71 and standard error of prediction (SEP) of 28.7 mg/dL. Of the 323 total data, 71.5% were in the A zone, 28.5% were in the B zone, and none were in the C, D, and E zones for the Clarke error-grid analysis. The prediction performance of the second stage was obtained as an r of 0.97 and SEP of 27.2 mg/dL. Of the 304 total data, 80.3% were in the A zone, 19.7% were in the B zone, and none were in the C, D, and E zones. These prediction results suggest that the new methodology has the potential to realize a noninvasive blood glucose monitoring system using near-infrared spectroscopy (NIRS) in ICUs. Although the total performance of the present monitoring system has not yet reached a satisfactory level as a stand-alone system, it can be developed as a complementary system to the conventional one used in ICUs for routine blood glucose management, which checks the blood glucose levels of patients every few hours.