Discrimination of psychoactive fungi (commonly called "magic mushrooms") based on the DNA sequence of the internal transcribed spacer region

'Magic mushrooms' (MMs) are psychoactive fungi containing the hallucinogenic compounds, psilocin (1) and psilocybin (2). Since June 6, 2002, these fungi have been regulated by the Narcotics and Psychotropics Control Law in Japan. Because there are many kinds of MMs and they are sold even as dry powders in local markets, it is very difficult to identify the original species of the MMs by morphological observation. Therefore, we investigated the internal transcribed spacer (ITS) region in the ribosomal RNA gene of MMs obtained in Japanese markets to classify them by a genetic approach. Based on the size and nucleotide sequence of the ITS region amplified by PCR, tested MMs were classified into 6 groups. Furthermore, a comparison of the DNA sequences of the MMs with those of authentic samples or with those found in the databases (GenBank, EMBL and DDBJ) made it possible to identify the species of tested MMs. Analysis by LC revealed that psilocin (1) was contained at the highest level in Panaeolus cyanescens among the MMs, but was absent in the Amanita species.     

Liquid crystalline elastomers: dynamics and relaxation of microstructure

The equilibrium mechanical response of nematic elastomers can be soft or hard depending on the relation between the imposed strains and the nematic director, in particular, if the local nematic director is able to respond by rotating. The dynamical response proves to be equally unusual. We examine the linear dynamic mechanical response of monodomain nematic elastomers under shear and the aspects of time-temperature superposition of the dynamical data across phase-transition regions. In the low-frequency region of the master curves, one finds a dramatic reduction of rubber plateau modulus and the rise in internal dissipation: in the shear geometries compatible with dynamic soft elasticity. Power-law variation of the storage modulus with frequency G' proportional, variant omega(a) agrees very well with the results of static stress relaxation, where each relaxation curve obeys the analogous power law G' proportional, variant t(-a) in the corresponding region of long times and temperatures.     

A novel anionic surfactant templating route for synthesizing mesoporous silica with unique structure

Anionic surfactants are used in greater volume than any other surfactants because of their highly potent detergency and low cost of manufacture. However, they have not been used as templates for synthesizing mesoporous silica. Here we show a templating route for preparing mesoporous silicas based on self-assembly of anionic surfactants and inorganic precursors. We use aminosilane or quaternized aminosilane as co-structure-directing agent (CSDA), which is different from previous pathways. The alkoxysilane site of CSDA is co-condensed with inorganic precursors; the ammonium site of CSDA, attached to silicon atoms incorporated into the wall, electrostatically interacts with the anionic surfactants to produce well-ordered anionic-surfactant-templated mesoporous silicas (AMS). These have new structures with periodic modulations as well as two-dimensional hexagonal and lamellar phases. The periodic modulations may be caused by the coexistence of micelles that differ in size or curvature, possibly owing to local chirality. These mesoporous silicas provide a new family of mesoporous materials as well as shedding light on the structural behaviour of anionic surfactants.     

Developmental word acquisition and grammar learning by humanoid robots through a self-organizing incremental neural network.

We present a new approach for online incremental word acquisition and grammar learning by humanoid robots. Using no data set provided in advance, the proposed system grounds language in a physical context, as mediated by its perceptual capacities. It is carried out using show-and-tell procedures, interacting with its human partner. Moreover, this procedure is open-ended for new words and multiword utterances. These facilities are supported by a self-organizing incremental neural network, which can execute online unsupervised classification and topology learning. Embodied with a mental imagery, the system also learns by both top-down and bottom-up processes, which are the syntactic structures that are contained in utterances. Thereby, it performs simple grammar learning. Under such a multimodal scheme, the robot is able to describe online a given physical context (both static and dynamic) through natural language expressions. It can also perform actions through verbal interactions with its human partner.     

Dependence of Seebeck coefficient on a load resistance and energy conversion efficiency in a thermoelectric composite

The thermo-emf ΔV and current ΔI generated by imposing the alternating temperature gradients (ATG) at a period of T and the steady temperature gradient (STG) on a thermoelectric (TE) composite were measured as a function of t, where t is the lapsed time and T was varied from 60 to or ∞ s. The STG and ATG were produced by imposing steadily and alternatively a source voltage V in the range from 1.0 to 4.0 V on two Peltier modules sandwiching a composite. ΔT, ΔV, ΔI and V_P oscillate at a period T and their waveforms vary significantly with a change of T, where ΔV and V_P are the voltage drops in a load resistance R_L and in resistance R_P of two modules. The resultant Seebeck coefficient |α| = |ΔV|/ΔT of a composite under the STG was found to be expressed as |α| = |α₀|(1 − R_comp/R_T), where R_T is the total resistance of a circuit for measuring the output signals and R_comp is the resistance of a composite. The effective generating power ΔW_eff has a local maximum at T = 960 s for the p-type composite and at T = 480 s for the n-type one. The maximum energy conversion efficiency η of the p- and n-type composites under the ATG produced by imposing a voltage of 4.0 V at an optimum period were 0.22 and 0.23% at ΔT_eff = 50 K, respectively, which are 42 and 43% higher than those at ΔT = 42 K under the STG. These maximum η for a TE composite sandwiched between two Peltier modules, were found to be expressed theoretically in terms of R_P, R_T, R_L, α_P and α, where α_P and α are the resultant Seebeck coefficients of Peltier modules and a TE composite.     

A Gait Phase Measurement System Using Treadmill Motor Current

The article describes the development of a gait phase time-based split-belt treadmill measurement system. Conventional methods of measuring gait phase, such as the foot switch and force plate, require significant preparation and are costly. In this article, we propose a simple, cheap, and accurate gait phase measurement system that utilizes only the treadmill motor current value. Comparison of this algorithm with conventional methods reveals that the proposed algorithm is as accurate as the foot switch. Moreover, the proposed algorithm can estimate stance phase within a 0.2?s error of the measured value of the force plate in most cases (four out of five healthy subjects). This accuracy is higher than that of the foot switch which is widely used in the clinical field.     

A speeded-up online incremental vision-based loop-closure detection for long-term SLAM

An online incremental method of vision-only loop-closure detection for long-term robot navigation is proposed. The method is based on the scheme of direct feature matching which has recently become more efficient than the Bag-of-Words scheme in many challenging environments. The contributions of the paper are the application of hierarchical k-means to speed-up feature matching time and the improvement of the score calculation technique used to determine the loop-closing location. As a result, the presented method runs quickly in long term while retaining high accuracy. The searching cost has been markedly reduced. The proposed method requires no any off-line dictionary generation processes. It can start anywhere at any times. The evaluation has been done on standard well-known datasets being challenging in perceptual aliasing and dynamic changes. The results show that the proposed method offers high precision-recall in large-scale different environments with real-time computation comparing to other vision-only loop-closure detection methods.     

Supercritical fluid extraction of fungal oil using CO2, N2O,CHF3 and SF6

The extraction of oil from fungi (Mortierella ramanniana var.angulispora) was studied using carbon dioxide (CO₂), nitrous oxide (N₂O), trifluoromethane (CHF₃) and sulfur hexafluoride (SF₆) under supercritical conditions. The oil solubility was highest in SC-N₂O followed by SC-CO₂, while both SC-CHF₃ and SC-SF₆ showed poorer solvent power. The recorded oil solubilities at 333 K and 24.5 MPa were 2.3 wt% in N₂O, 0.48 wt% in CO₂, 0.0099 wt% in CHF₃ and 0.0012 wt% in SF₆. The oil solubilities in SC-N₂O and SC-CO₂ were measured over the pressure range 15.7–29.4 MPa and at temperatures ranging from 313–353 K. N₂O always showed greater solvent power than did CO₂ at the same temperature and pressure. The solvent power of a supercritical fluid increases with density at a given temperature, and increases with temperature at constant density. The change in neutral lipid composition of the extracted oil with the extraction ratio was measured. Free fatty acids or diglycerides were extracted more easily than triglycerides or sterol esters. The change in fatty acid composition was also measured. The proportion of γ-linolenic acid in the extract remained constant throughout the extraction.     

Adsorption properties of oxygen and methane on Ga-ZSM-5; the origin of the selectivity of NOx reduction using methane

The adsorption properties of oxygen and methane on Ga-ZSM-5 and Cu-ZSM-5 catalysts were examined by a TPD method to clarify the extraordinary selectivity of HC-SCR using methane on Ga-ZSM-5. It was observed that Ga-ZSM-5 did not adsorb oxygen but adsorbed methane dissociatively, while on Cu-ZSM-5 oxygen was dissociatively adsorbed and reacted with adsorbed ethylene.