Crystal orientation of β-phase isotactic polypropylene induced by magnetic orientation of N,N′-dicyclohexyl-2,6-naphthalenedicarboxamide

Melt crystallization of isotactic polypropylene (iPP), containing crystallites of N,N′-dicyclohexyl-2,6-naphthalenedicarboxamide (DCNDCA) as a nucleating agent of the the β-phase iPP crystal, is carried out under a magnetic field (6 T) to obtain the alignment of the iPP crystal induced by magnetic alignment of DCNDCA. In a previous paper, DCNDCA was reported to undergo magnetic alignment in a liquid suspension. The obtained iPP sample exhibits alignment of the β-phase crystal with the c-axis aligned perpendicular to the magnetic field. The comparison of this alignment of iPP with the reported magnetic alignment of DCNDCA indicates that the β-phase crystal grows epitaxially on the DCNDCA crystal. The (330)_β plane of the iPP crystal lies on the bc-plane of the DCNDCA crystal in which the direction of the c-axis of the iPP coincides with the direction of the b-axis of the DCNDCA crystal.     

Additional kernel observer: privilege escalation attack prevention mechanism focusing on system call privilege changes

International Journal of Information Security - Cyberattacks, especially attacks that exploit operating system vulnerabilities, have been increasing in recent years. In particular, if administrator...     

Pervaporation via silicon-based membranes: Correlation and prediction of performance in pervaporation and gas permeation

Pervaporation (PV) is a membrane technology that holds great promise for industrial applications. To better understand the PV mechanism, PV dehydrations of various types of organic solvents (methanol, ethanol, iso-propanol, tert-butanol, and acetone) were performed on five types of organosilica and two types of silicon carbide-based membranes, all with different pore sizes. Water permeance was dependent on the types of organic aqueous solutions, which suggested that organic solvents penetrated the pores and hindered the permeation of water. In addition, water permeance of various types of membranes in PV was well correlated with hydrogen permeance in single-gas permeation. Furthermore, a clear correlation was obtained between the permeance ratio in PV and that in single-gas permeation, which was confirmed via the modified-gas translation model. These correlations make it possible to use single-gas permeation properties to predict PV performance.     

Spatial distribution of silica fillers in phase-separated rubber blends investigated by three-dimensional elemental mapping

The distribution of nano-sized silica in binary rubber blends is characterized by scanning transmission electron microscopy (STEM) tomography combined with energy dispersive X-ray spectrometry (EDX). 3D distribution of silica is visualized by STEM-EDX tomography with the tilt-series of silicon elemental maps, while the phase-separated morphologies of polyisoprene rubber (IR) and styrene-butadiene rubber (SBR) are visualized by STEM-tomography in high-angle-annular-dark field (HAADF) mode. The combination of STEM-EDX and STEM-HAADF tomography enables us to determine the distribution of silica between the two rubber phases quantitatively even with high contents of silica up to 70 phr (weight parts per hundred rubber). It is found that silica is preferentially distributed in the SBR phase, but it is also distributed in the IR phase when the IR fraction in the total rubber components is higher than 40 wt%. The preferential distribution of silica in the SBR phase improves the dispersion of the IR domains. This is the first use of this technique for a multicomponent polymer system, showing the advantage to characterize the complicated multicomponent polymer composite morphologies.     

Development of a flexible autonomous robot without sensors or controllers

Recently, various robots with many degrees of freedom, such as rescue robots and domestic robots, have been developed and used in practical applications. It is difficult to control such robots autonomously in real environments, because in order to control the many degrees of freedom, we have to observe many states, calculate huge amounts of information, and operate many actuators. In this study, we consider a flexible robot without sensors or controllers that can determine the inclination of a slope and climb up the slope. In order to demonstrate the effectiveness of the proposed framework, we have developed a prototype robot and conducted experiments. The result indicates that the robot could determine the inclination and climb up a gentle slope autonomously. Thus, we have realized an autonomous robot that has no explicit sensors or controllers.     

Estimation of time-dependent input from neuronal membrane potential

The set of firing rates of the presynaptic excitatory and inhibitory neurons constitutes the input signal to the postsynaptic neuron. Estimation of the time-varying input rates from intracellularly recorded membrane potential is investigated here. For that purpose, the membrane potential dynamics must be specified. We consider the Ornstein-Uhlenbeck stochastic process, one of the most common single-neuron models, with time-dependent mean and variance. Assuming the slow variation of these two moments, it is possible to formulate the estimation problem by using a state-space model. We develop an algorithm that estimates the paths of the mean and variance of the input current by using the empirical Bayes approach. Then the input firing rates are directly available from the moments. The proposed method is applied to three simulated data examples: constant signal, sinusoidally modulated signal, and constant signal with a jump. For the constant signal, the estimation performance of the method is comparable to that of the traditionally applied maximum likelihood method. Further, the proposed method accurately estimates both continuous and discontinuous time-variable signals. In the case of the signal with a jump, which does not satisfy the assumption of slow variability, the robustness of the method is verified. It can be concluded that the method provides reliable estimates of the total input firing rates, which are not experimentally measurable.     

Analysis of PD-generated SF/sub 6/ decomposition gases adsorbed on carbon nanotubes

Chemical byproducts analysis has been recognized as a powerful diagnosis method for SF₆ gas-insulated switchgear (GIS). The authors have previously demonstrated that a carbon nanotube (CNT) gas sensor could detect partial discharge (PD) generated in SF₆ gas. However, PD-generated decomposition gas species, which were responsible for the CNT gas sensor response, have not been identified yet. In this paper, two kinds of experiments were conducted in order to identify the responsible decomposition gas species. At first, the decomposition gas molecules adsorbed on CNTs were analyzed by Fourier transformation infrared (FTIR) spectroscopy. FTIR absorbance was observed around 735 cm^-1 after CNTs were exposed to PD generated in SF₆. In the second experiment, the CNT gas sensor responses to typical SF₆ decomposition products (HF and SF₄) were examined. The CNT gas sensor responded to these gases in the same way as to PD generated in SF₆. SF₄ response was larger than HF response. Based on these results, SF ₄ and SOF₂ emerged as candidates for the responsible decomposition gases. Electrochemical interactions between adsorbed gas molecules and CNT were discussed based on theoretical predictions of molecular orbital calculations. The calculation results suggested that both of SOF₂ and SF₄ could increase the CNT gas sensor conductance     

Properties of Hopfield model with the zero-order synaptic decay

In this paper, we investigate the effect of synaptogenesis on memories in the brain, using the abstract-associative memory model, Hopfield model with the zero-order synaptic decay. Using the numerical simulation, we demonstrate the possibility that synaptogenesis plays a role in maintaining recent memories embedded in the network while avoiding overloading. For the network consisting of 1000 units, it turned out that the minimum decay rate to avoid overloading is 0.02, and the optimal decay rate to maximize the storage capacity is 0.08. We also show that the average numbers of replacement synapses at each learning step corresponding to these two values are 1187 and 21024, respectively.     

A study on physical and mechanical properties for soft to firm clays in Yangon area – Properties of clays deposit at the sedimentary basins in Myanmar

Recently, a great deal of foreign investment has been entered into construction of the social infrastructure of Myanmar. Many construction projects are therefore on-going, and these are especially planned in the Yangon area. While these construction booms are increasing, existing studies on the geotechnical problems in the Yangon area such as problematic soils like soft clays are limited at present. Information on soil properties has also not been shared and has been confined to individual projects. In this paper, the boring and laboratory tests carried out in the Yangon area are selected and focused upon among the tests carried out in Myanmar. Laboratory test results for clay deposits in the Yangon area are analyzed and the differences in soil properties between different sedimentary basins and sub-areas divided by the Tertiary sediment ridge that runs from north to south at the center of Yangon are clarified together with a comparison to the clays found in other countries, which have been previously investigated.