Revealing microbial community structures in large- and small-scale activated sludge systems by barcoded pyrosequencing of 16S rRNA gene

The diversity of bacterial groups in activated sludge from large- and small-scale wastewater treatment plants was explored by barcoded pyrosequencing of 16S rRNA gene. Activated sludge samples (three small and 17 large scale) were collected from 12 wastewater treatment plants to clarify precise taxonomy and relative abundances. DNA was extracted, and amplified by 4 base barcoded 27f/519r primer set. The 454 Titanium (Roche) pyrosequences were obtained and analyses performed by Quantitative Insight Into Microbial Ecology (QIIME) with around 100,000 reads. Sequence statistics were computed, while constructing a phylogenetic tree and heatmap. Computed results explained total microbial diversity at phylum and class level and resolution was further extended to Operational Taxonomic Unit (OTU) based taxonomic assignment for investigating community distribution based on individual sample. Composition of sequence reads were compared and microbial community structures for large- and small-scale treatment plants were identified as major phyla (Proteobacteria and Bacteroidetes) and classes (Betaproteobacteria and Bacteroidetes). Also, family level breakdowns were explained and differences in family Nitrospiraceae and phylum Actinobacteria found at their species level were also illustrated. Thus, the pyrosequencing method provides high resolution insight into microbial community structures in activated sludge that might have been unnoticed with conventional approaches.     

Multi-modal Information Integration for Interactive Multi-agent Systems

This paper proposes a multi-agent system that carries out cooperative work. To achieve this, we use Fuzzy Associative Memory Organizing Unit Systems (FAMOUS) and Conceptual Fuzzy Sets (CFS). By using these proposed methods, each agent robot can decide its own behaviour to suit the situation in its environment. We apply this system to an Intelligent Transportation System (ITS) and do simulations.     

Current dependence of performance of TES microcalorimeters and characteristics of excess noise

We are developing transition edge sensor (TES) microcalorimeter arrays for future Japanese astronomy missions. Although 6.6 eV energy resolution for 5.9 keV and 74 μs decay time are achieved, our energy resolution was limited by the excess noise of unknown origin. The dominant noise showed 1/R dependence and it only appeared when the current through the TES, I, is larger than 10 μA. This is explained if we assume a constant voltage noise source with a level of 2(4kT_CR_n)^1/2. We also investigated the influence of I on the TES performance and found the TES sensitivity is reduced when the ratio of current to the critical current I/I_C is large. It can explain the reduction of observed when operated without a magnetic shield. We also found a strong correlation between I_C and or the baseline width. Thus, we conclude that I_C is an essential parameter for the TES performance.     

Syndiotactic‐specific radical polymerization of N‐isopropylacrylamide in toluene at low temperatures in the presence of silyl alcohols

The radical polymerization of N‐isopropylacrylamide was carried out in toluene at low temperatures in the presence of silyl alcohols, such as triethylsilanol. Poly(N‐isopropylacrylamide) with a racemo dyad content of 75% was obtained at ? 80 °C with a 4:1 triethylsilanol to monomer ratio loading. NMR analysis suggests that the mechanism for syndiotactic induction, in the presence of silyl alcohols, may be similar to that observed with alkyl alcohols. In this case, a 1:2 complex formation, via hydrogen bonding interactions, leads to the induction of syndiotactic specificity. Copyright © 2012 Society of Chemical Industry     

Te concentration dependent photoemission and inverse-photoemission study of FeSe1?xTex

We have characterized the electronic structure of FeSe_1−xTe_x for various x values using soft x-ray photoemission spectroscopy (SXPES), high-resolution photoemission spectroscopy (HRPES) and inverse photoemission spectroscopy (IPES). The SXPES valence band spectral shape shows that the 2 eV feature in FeSe, which was ascribed to the lower Hubbard band in previous theoretical studies, becomes less prominent with increasing x. HRPES exhibits systematic x dependence of the structure near the Fermi level (E_F): its splitting near E_F and filling of the pseudogap in FeSe. IPES shows two features, near E_F and approximately 6 eV above E_F; the former may be related to the Fe 3d states hybridized with chalcogenide p states, while the latter may consist of plane-wave-like and Se d components. In the incident electron energy dependence of IPES, the density of states near E_F for FeSe and FeTe has the Fano lineshape characteristic of resonant behavior. These compounds exhibit different resonance profiles, which may reflect the differences in their electronic structures. By combining the PES and IPES data the on-site Coulomb energy was estimated at 3.5 eV for FeSe.     

Gain and phase margin of optimal memoryless regulator of systems with time-delay

A class of linear quadratic regulators of the system with time-delay in the states is constructed by a memoryless feedback, and its robustness is evaluated. First, a static non-linear perturbation is inserted in the input channel, and a robust stability condition is derived. As its special case, it is shown that the regulator has infinite gain margin and at least 50% gain reduction tolerance. Next, a dynamic linear perturbation is inserted in the same point, and an alternative stability condition is derived. It assures that the regulator has at least 60o phase margin. These results coincide with those of the finite dimensional LQ regulator.     

Extraction of Trivalent Rare Earths and Minor Actinides from Nitric Acid with N,N,N’,N’-Tetradodecyldiglycolamide (TDdDGA) by Using Mixer-Settler Extractors in a Hot Cell

Single-stage batch experiments to reveal the extraction properties of N,N,N’,N’-tetradodecyldiglycolamide (TDdDGA) for Y, La, Eu, Nd, and Am in nitric acid were carried out. The distribution ratios of Y, Eu, Nd, and Am exceeded 10 when the nitric acid concentration was 1–2 mol/dm³ (M), and the distribution ratio of La was 5.5 when the nitric acid concentration was 2 M. A continuous counter-current experiment using 0.1 M TDdDGA diluted with n-dodecane was performed using mixer-settler extractors installed in a hot cell. Nitric acid with a concentration of 2.1 M containing minor actinides (MAs: Am and Cm), rare earths (REs: Y, La, Nd, and Eu), and other fission products (Sr, Cs, Zr, Mo, Ru, Rh, and Pd) was fed to the extractor. TDdDGA effectively extracted MAs and REs from the feed, while other fission products were barely extracted. The extracted MAs and REs were back-extracted by bringing them in contact with 0.02 M nitric acid, and they were collected as the MA–RE fraction. The results indicated that more than 98% of Am and Cm in the feed were recovered in the MA–RE fraction. The proportions of Y, La, Nd, and Eu in the MA–RE fraction were 94.0%, 99.9%, 99.9%, and 86.9%, respectively.     

Evaluation of standing‐sitting support system with passive rotational seat mechanism in standing motion

Since a decrease in muscle mass of elderly people, the physical burden of them in standing‐sitting motion of a seat are increasing than young people. For this problem, several standing‐sitting support systems have been developed, and evaluations of these systems focusing on a reduction of physical load have been discussed. However, these evaluations are of support systems with an active actuators or of support systems when they use a handrail and a standing aid. Thus, an evaluation of a support system with only passive actuators has not been reported. In this paper, in standing motion with using a standing‐sitting support system with passive rotational seat mechanism which our group proposes, we objectively evaluate an effectiveness of the passive rotational seat mechanism by statistical analysis.     

Data-efficient learning of robotic clothing assistance using Bayesian Gaussian process latent variable model

ABSTRACT

Motor-skill learning for complex robotic tasks is a challenging problem due to the high task variability. Robotic clothing assistance is one such challenging problem that can greatly improve the quality-of-life for the elderly and disabled. In this study, we propose a data-efficient representation to encode task-specific motor-skills of the robot using Bayesian nonparametric latent variable models. The effectivity of the proposed motor-skill representation is demonstrated in two ways: (1) through a real-time controller that can be used as a tool for learning from demonstration to impart novel skills to the robot and (2) by demonstrating that policy search reinforcement learning in such a task-specific latent space outperforms learning in the high-dimensional joint configuration space of the robot. We implement our proposed framework in a practical setting with a dual-arm robot performing clothing assistance tasks.