Matrix influence on the piezoelectric properties of piezoelectric ceramic/polymer composite exhibiting particle alignment

This study was addressed to the influence of an electric field strength applied at fabrication process and matrix properties, such as the dielectric constant and the Young's modulus, on “pseudo‐1‐3 piezoelectric ceramic/polymer composite” in order to further enhance the piezoelectricity of that. The pseudo‐1‐3 piezoelectric ceramic/polymer composite consists of linearly ordered piezoelectric ceramic particles in polymer material. Silicone gel, silicone rubber, urethane rubber, and poly‐methyl‐methacrylate, which exhibit different dielectric constants and Young's modulus, were used as matrices to evaluate the matrix influence. The piezoelectricity of the pseudo‐1‐3 piezoelectric ceramic/polymer composite was evaluated using the piezoelectric strain constant d₃₃. The d₃₃ is one of the indices of the piezoelectric properties for piezoelectric materials. As a result, it was confirmed that d₃₃ of the pseudo‐1‐3 piezoelectric ceramic/polymer composite increased with the increase of the electric filed strength applied at fabrication process, though, it reached a constant value at a certain strength value. Further it was confirmed that dielectric constant of the matrix had a small influence on d₃₃ of the pseudo‐1‐3 piezoelectric ceramic/polymer composite, however, in case of matrix of lower Young's modulus, d₃₃ was increase. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41817.     

Large magnetoresistivity of sputtered Al-(O or N)-Bi alloys

Application of the sputtering technique to (Al₂O₃)_xBi_100–x and (AIN)_x Bi_100–x (x = 0 to 100%) has been found to result in the formation of a duplex material consisting of hexagonal bismuth particles dispersed finely and homogeneously in amorphous Al_xO_y and Al_xN_y matrices. The particle size and interparticle distance of the bismuth phase were about 5 to 140nm and 5 to 35 nm. The duplex alloys have high electrical resistivities ranging from 1.82 × 10³ to 3.16 × 10⁵ cm combined with a negative temperature-dependent resistivity of 148 to 342% of ₂₇₃. Furthermore, all the Al-O-Bi and Al-N-Bi alloys have been found to exhibit a positive magnetoresistive change and the maximum value, (H), at 4.2 K and 7.5T reaches 5.85 × 10⁴ cm for (Al-O)_65.7Bi_34.3 and 1.99 × 10⁵ cm for (Al-N)_69.7 Bi_30.3. The large magnetoresistivities are probably due to the unique sputtered structure consisting of metallic bismuth particles with a long mean free path of electrons embedded finely and homogeneously in amorphous Al_xO_y or Al_xN_y matrix, resulting in the large difference of the relaxation times (different mobilities) of electron carriers. It has thus been demonstrated that the oxide- or nitride-based composite materials exhibiting large magnetoresistivities, which cannot be achieved in metallic composite materials, are obtained by sputtering simultaneously Al₂O₃ or AIN and bismuth which is immiscible to aluminium.     

Adsorption of urea,creatinine, and uric acid from three solution types using spherical activated carbon and its recyclability

In this paper, we propose that the urinary toxins from the wastewater be adsorbed on an adsorbent such as spherical activated carbon and the latter be regenerated by subjecting it to high temperatures to recycle activated carbon and also to recycle the water used in dialysis. We studied the adsorption of artificial waste dialysate, which is a mixed solution of urea, creatinine, and uric acid, and the separate solutions for each of these and found that their extents of adsorption onto the spherical activated carbon material were nearly identical. The amount of adsorption was approximately 1.4 mg·g^-1 for urea, 18 mg·g^-1 for creatinine, and 20 mg·g^-1 for uric acid. The urea, creatinine, and uric acid adsorbed onto the spherical activated carbon decomposed on heat treatment at 500℃, and the adsorption capacity of the spherical activated carbon was regenerated. Our study successfully demonstrated that the spherical activated carbon can be recycled in the waste dialysate treatment process.     

Identification of Tumor Suppressive Genes Regulated by miR-31-5p and miR-31-3p in Head and Neck Squamous Cell Carcinoma

We identified the microRNA (miRNA) expression signature of head and neck squamous cell carcinoma (HNSCC) tissues by RNA sequencing, in which 168 miRNAs were significantly upregulated, including both strands of the miR-31 duplex (miR-31-5p and miR-31-3p). The aims of this study were to identify networks of tumor suppressor genes regulated by miR-31-5p and miR-31-3p in HNSCC cells. Our functional assays showed that inhibition of miR-31-5p and miR-31-3p attenuated cancer cell malignant phenotypes (cell proliferation, migration, and invasion), suggesting that they had oncogenic potential in HNSCC cells. Our in silico analysis revealed 146 genes regulated by miR-31 in HNSCC cells. Among these targets, the low expression of seven genes (miR-31-5p targets: CACNB2 and IL34; miR-31-3p targets: CGNL1, CNTN3, GAS7, HOPX, and PBX1) was closely associated with poor prognosis in HNSCC. According to multivariate Cox regression analyses, the expression levels of five of those genes (CACNB2: p = 0.0189; IL34: p = 0.0425; CGNL1: p = 0.0014; CNTN3: p = 0.0304; and GAS7: p = 0.0412) were independent prognostic factors in patients with HNSCC. Our miRNA signature and miRNA-based approach will provide new insights into the molecular pathogenesis of HNSCC.     

Catalyst Design of Pt-Modified Ni/Al2O3 Catalyst with Flat Temperature Profile in Methane Reforming with CO2 and O2

Pt(0.3)/Ni(10)/Al₂O₃, prepared by a sequential impregnation method, exhibited a more excellent performance in methane reforming with CO₂ and O₂ in terms of the catalytic activity and the temperature profile of the catalyst bed than Pt(0.3) + Ni(10)/Al₂O₃ prepared by a coimpregnation method, Ni(10)/Al₂O₃, Pt(0.3)/Al₂O₃, and Pt(10)/Al₂O₃. It is thought that this is because the surface Pt atoms on Ni catalyst can contribute to the enhancement of the catalyst reducibility.     

Construction of living cellular automata using the Physarum plasmodium

The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has an amorphous cell body. To clearly observe how the plasmodium makes decisions in its motile and exploratory behaviours, we developed a new experimental system to pseudo-discretize the motility of the organism. In our experimental space that has agar surfaces arranged in a two-dimensional lattice, the continuous and omnidirectional movement of the plasmodium was limited to the stepwise one, and the direction of the locomotion was also limited to four neighbours. In such an experimental system, a cellular automata-like system was constructed using the living cell. We further analysed the exploratory behaviours of the plasmodium by duplicating the experimental results in the simulation models of cellular automata. As a result, it was revealed that the behaviours of the plasmodium are not reproduced by only local state transition rules; and for the reproduction, a kind of historical rule setting is needed.     

Incremental learning of gestures for human–robot interaction

For a robot to cohabit with people, it should be able to learn people’s nonverbal social behavior from experience. In this paper, we propose a novel machine learning method for recognizing gestures used in interaction and communication. Our method enables robots to learn gestures incrementally during human–robot interaction in an unsupervised manner. It allows the user to leave the number and types of gestures undefined prior to the learning. The proposed method (HB-SOINN) is based on a self-organizing incremental neural network and the hidden Markov model. We have added an interactive learning mechanism to HB-SOINN to prevent a single cluster from running into a failure as a result of polysemy of being assigned more than one meaning. For example, a sentence: “Keep on going left slowly” has three meanings such as, “Keep on (1)”, “going left (2)”, “slowly (3)”. We experimentally tested the clustering performance of the proposed method against data obtained from measuring gestures using a motion capture device. The results show that the classification performance of HB-SOINN exceeds that of conventional clustering approaches. In addition, we have found that the interactive learning function improves the learning performance of HB-SOINN.     

HSPF Simulation of Runoff and Sediment Loads in the Upper Changjiang River Basin, China

To evaluate the performance of a computer model simulating runoff and sediment load in the upper region of the Changjiang (Yangtze River) basin over a relatively short time interval, including examining the applicability of the input precipitation data generated from global circulation models and satellite data, we used a spatially distributed model, HSPF with the International Satellite Land Surface Climatology Project (ISLSCP) precipitation data for 1987 and 1988 as input data. The Nash–Sutcliffe coefficient (R2) for 5-day average streamflow was 0.94 in the calibration period and 0.95 in the verification period for the whole upper region. Moreover, the model simulated the 5-day average streamflow well in each main tributary, as shown by R2 values of 0.46–0.96, except that it underestimated the peak flow rates during the flood season over 2 years by up to 71% in Tuojiang and 61% in Jialingjiang. The model simulated the 5-day concentrations of suspended solids (SS) fairly well in the headwaters and upper regions of the Jinshajiang, Yalongjiang, and Minjiang watersheds, as shown by R2 values of 0.31–0.65. In the other regions, however, the model underestimated the SS load by up to 72%, and rarely simulated the fluctuation of SS concentration in each river channel during the flood season. These errors led to the underestimation of sediment runoff volume from the whole upper region during the flood season, as shown by the ratio of the simulated sediment load to the observed data at Yichang: 0.69 in the calibration period and 0.68 in the verification period. The ISLSCP precipitation tended to be more frequent and less intense than the measured precipitation. This was probably the main reason why the HSPF did not perform well in all regions at all times.     

Route guidance by a car navigation system based on augmented reality

Car navigation systems play a prominent role in road traffic safety and traffic regulation. However, it is necessary to improve the route guidance of car navigation systems so that they accurately and quickly recognize small differences in location. Thus, to increase the ease of understanding and safety of car navigation systems, navigation systems based on augmented reality have been proposed for providing guidance at road intersections. We are currently developing a car navigation system based on augmented reality, called AR‐Navi. We investigated designs for the display of road intersection guidance that can be easily understood even when limited information is available and proposed a “best shot” display method that does not use moving images. In addition, we implemented a prototype system that includes these methods and conducted driving experiments on public roads to evaluate the ease of understanding and safety of AR‐Navi. Using the evaluation results, we confirmed that the ease of understanding and safety is similar in the case of AR‐Navi and CG‐Navi. We also clarified the characteristics of AR‐Navi. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 180(2): 43–54, 2012; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22278     

Bag of local landscape features for fitness landscape analysis

Evolutionary computation is a research field dealing with black-box and complex optimization problems whose fitness landscapes are usually unknown in advance. It is difficult to select an appropriate evolutionary algorithm and parameters for a given problem due to the black-box setting although many evolutionary algorithms have been developed. In this context, several landscape features have been proposed and their usefulness examined for understanding the problem. In this paper, we propose a novel feature vector by focusing on the local landscape in order to characterize the fitness landscape. The proposed landscape features are a vector form and composed of a histogram of quantized local landscape features. We introduce two implementation methods of this concept, called the bag of local landscape patterns (BoLLP) and the bag of evolvability (BoEvo). The BoLLP uses the fitness pattern of the neighbors of a certain candidate solution, and the BoEvo uses the number of better candidate solutions in the neighbors as the local landscape features. Furthermore, the hierarchical versions of the BoLLP and the BoEvo, concatenated feature vectors with different sample sizes, are considered to capture the landscape characteristic with various resolutions. We extract the proposed landscape feature vectors from well-known continuous optimization benchmark functions and the BBOB benchmark function set to investigate their properties; the visualization of the proposed landscape features, clustering and running time prediction experiments are conducted. Then the effectiveness of the proposed landscape features for the fitness landscape analysis is discussed based on the experimental results.