Physical characteristics of sweet potato pulp/polycaprolactone blends

Sweet potato pulp (SSP) obtained as a by‐product from starch extraction was blended with polycaprolactone (PCL) to prepare a biodegradable plastic material. In the blends, PCL was used as a reinforcing agent. The SPP/PCL blends were prepared by compression‐molding under high temperature and pressure, at different SPP/PCL ratios, and the mechanical properties of the molded specimens were tested. Matrix structure and thermal properties were measured by using a Fourier transform infrared (FTIR) spectrophotometer, scanning electron microscope (SEM), differential scanning calorimetry (DSC), and thermogravimetric analyzer (TGA). Mechanical properties (tensile and flexural properties) were also measured to find the most suitable ratio in a SSP/PCL blend. During compression molding of the SPP/PCL blends under high pressure and temperature, chemical reaction occurred between SPP and PCL, and thus, thermal stability and mechanical strength of the blends increased and water uptake decreased. Also, by increasing the PCL content in the blend, the matrix in the blend became more homogeneous, and consequently, mechanical strength of the molded specimen increased. At 7/3 or 6/4 weight ratio of SSP/PCL, water uptake of the molded specimen became substantially less than that at 8/2. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 861–866, 2004     

Application of supercritical fluid chromatography in the quantitative analysis of minor components (carotenes,vitamin E,sterols, and squalene) from palm oil

The application of supercritical fluid chromatography (SFC) coupled with a UV variable-wavelength detector to isolate the minor components (carotenes, vitamin E, sterols, and squalene) in crude palm oil (CPO) and the residual oil from palm-pressed fiber is reported. SFC is a good technique for the isolation and analysis of these compounds from the sources mentioned. The carotenes, vitamin E, sterols, and squalene were isolated in less than 20 min. The individual vitamin E isomers present in palm oil were also isolated into their respective components, α-tocopherol, α-tocotrienol, γ-tocopherol, γ-tocotrienol, and δ-tocotrienol. Calibration of all the minor components of palm as well as the individual components of palm vitamin E was carried out and was found to be comparable to those analyzed by other established analytical methods.     

Resistivity and thermal reproducibility of carbon black and metallic powder filled silicone rubber heaters

Flexible heaters were prepared by extruding platinum‐catalyzed silicone rubber composites with conductive carbon black (CB) and metallic fillers. The conductor resistivity of the extruded heaters decreased in order of conductive titanium dioxide (TiO₂) > aluminum powder ≈ zinc powder > copper powder. Thermoelectric switching phenomena were investigated for the silicone rubber/CB/metallic powder systems. The positive temperature coefficient effect was dependent mainly on the CB content rather than on the content of the metallic powders. Resistivity and thermal reproducibility of the extruded heaters were also investigated by periodically applying AC voltage of 110 V. The heaters containing copper and TiO₂ powders exhibited excellent electrical reproducibility. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 95: 1122–1128, 2005     

Time and shear dependent rheology of maleated polyethylene and its nanocomposites

Dipole-dipole and/or hydrogen-bonding interactions between the pendant functional groups within maleated high-density polyethylene (PE-g-MAn) establish a physical polymer network, whose formation kinetics and shear-sensitivity are revealed by dynamic oscillatory testing. The pronounced time and shear dependent viscoelastic properties of PE-g-MAn were not observed for a corresponding imide derivative, PE-g-imide, presumably due to weakened functional group associations in the latter material.The melt compounding of PE-g-MAn with onium-ion exchanged montmorillonite clay (NR₄⁺-MM) resulted in a partially exfoliated hybrid nanocomposite structure, whose viscoelastic behaviour differed significantly from that of the unfilled polymer. The presence of dispersed clay platelets altered the extent of functional group associations, thereby changing the dynamics of network formation.     

Performance of fluorine-added CoMoS/Al2O3 prepared by sonochemical and chemical vapor deposition methods in the hydrodesulfurization of dibenzothiophene and 4,6-dimethyldibenzothiophene

The performance of a new type of CoMoS/Al₂O₃ catalyst, with added fluorine and prepared by sonochemical and chemical vapor deposition (CVD) methods, was investigated in the hydrodesulfurization (HDS) of dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (4,6-DMDBT). The catalyst, which was designed to contain optimum amounts of fluorine and cobalt, exhibited a higher activity, ca. 4.6 times higher activity particularly in the HDS of 4,6-DMDBT, than a fluorine-free catalyst prepared by a conventional impregnation method. The enhanced activity of the new catalyst can be attributed to the cumulative effects of individual factors involved in the catalyst preparation. That is, the use of a sonochemical synthesis led to a high dispersion of small MoS₂ crystallites on the alumina, and the addition of the Co species to the catalyst by CVD caused a close interaction between the Co species and the MoS₂ crystallites to produce numerous CoMoS species, which are the catalytically active species for HDS. The addition of fluorine increased the amounts of acidic sites in the catalyst, which promoted hydrogenation (HYD) route to a greater extent than the direct desulfurization (DDS) route in DBT HDS and both HYD and DDS routes to similar extents in the case of 4,6-DMDBT HDS. Accordingly, the addition of fluorine led to a greater increase in catalytic activity for 4,6-DMDBT HDS than for DBT HDS.     

Change of short-term memory effect in acute ischemic ventricular myocardium: A computational study

The ionic mechanism of change in short-term memory (STM) during acute myocardial ischemia has not been well understood. In this paper, an advanced guinea pig ventricular model developed by Luo and Rudy was used to investigate STM property of ischemic ventricular myocardium. STM response was calculated by testing the time to reach steady-state action potential duration (APD) after an abrupt shortening of basic cycling length (BCL) in the pacing protocol. Electrical restitution curves (RCs), which can simultaneously visualize multiple aspects of APD restitution and STM, were obtained from dynamic and local S1S2 restitution portrait (RP), which consist of a longer interval stimulus (S1) and a shorter interval stimulus (S2). The angle between dynamic RC and local S1S2 RC reflects the amount of STM. Our results indicated that compared with control (normal) condition, time constant of STM response in the ischemic condition decreased significantly. Meanwhile the angle which reflects STM amount is less in ischemic model than that in control model. By tracking the effect of ischemia on intracellular ion concentration and membrane currents, we declared that changes in membrane currents caused by ischemia exert subtle influences on STM; it is only the decline of intracellular calcium concentration that give rise to the most decrement of STM.     

Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease

Amnestic mild cognitive impairment (aMCI) often is an early stage of Alzheimer's disease (AD). MCI is characterized by cognitive decline departing from normal cognitive aging but that does not significantly interfere with daily activities. This study explores the potential of scalp EEG for early detection of alterations from cognitively normal status of older adults signifying MCI and AD. Resting 32-channel EEG records from 48 age-matched participants (mean age 75.7 years)—15 normal controls (NC), 16 early MCI, and 17 early stage AD—are examined. Regional spectral and complexity features are computed and used in a support vector machine model to discriminate between groups. Analyses based on three-way classifications demonstrate overall discrimination accuracies of 83.3%, 85.4%, and 79.2% for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. These results demonstrate the great promise for scalp EEG spectral and complexity features as noninvasive biomarkers for detection of MCI and early AD.     

An effective dissimilarity measure for clustering of high-dimensional categorical data

Clustering is to group similar data and find out hidden information about the characteristics of dataset for the further analysis. The concept of dissimilarity of objects is a decisive factor for good quality of results in clustering. When attributes of data are not just numerical but categorical and high dimensional, it is not simple to discriminate the dissimilarity of objects which have synonymous values or unimportant attributes. We suggest a method to quantify the level of difference between categorical values and to weigh the implicit influence of each attribute on constructing a particular cluster. Our method exploits distributional information of data correlated with each categorical value so that intrinsic relationship of values can be discovered. In addition, it measures significance of each attribute in constructing respective cluster dynamically. Experiments on real datasets show the propriety and effectiveness of the method, which improves the results considerably even with simple clustering algorithms. Our approach does not couple with a clustering algorithm tightly and can also be applied to various algorithms flexibly.     

Composition pattern oriented tag extraction from short documents using a structural learning method

With the rapid growth of web, automatic tagging that detects informative terms from a document becomes an important problem for information aggregation and sharing services. In particular, automatic tagging for short documents becomes more interesting as many users are increasingly publishing information through social media services which encourage users to create the documents of short length. In this paper, we propose a novel automatic tagging model for short text documents from social media services, following the framework of supervised learning. We redefine traditional frequency-based term features so that they can address the properties of the documents created under length limitation and consider sequential dependencies between successive terms in a document based on a structural support vector machine. In addition, our proposed approach incorporates composition patterns by which users put informative terms into their documents. Extensive experiments have been conducted to validate the presented approach, and it was found that the proposed term features were effective for extracting tags, and the tag extractor trained by considering the sequential dependencies and composition patterns achieved superior performance results over the existing alternative methods.