Pipe Heating System with Underground Water Tank for Snow Thawing and Ice Prevention on Roads and Bridge Decks

In order to prevent traffic accidents on snow-covered bridge decks, the writers developed a new pipe heating system that uses only groundwater stored in a large underground tank. The underground tank provides geothermal energy, i.e., groundwater of constant temperature, through heating pipes embedded in concrete pavements with no electric heater or fuel boiler. The pipe heating system was constructed at approximately 50% of the cost of comparable systems. In addition, there is a reduction of 10% in operating costs compared with the previous system. The present paper outlines its design and construction and provides fundamental data for the developed system. The piped heating system has kept the road conditions safe during the winter season by always removing the snow and ice from the heated road and bridge sections earlier than the surrounding roads. According to long-term temperature measurements, this system has prevented the road temperature from decreasing below 0°C, even through nighttime and morning periods. This report presents the system as an economical and effective solution for snow thawing and ice prevention.     

In-vivo human brain molecular imaging with a brain-dedicated PET/MRI system

Advances in the new-generation of ultra-high-resolution, brain-dedicated positron emission tomography-magnetic resonance imaging (PET/MRI) systems have begun to provide many interesting insights into the molecular dynamics of the brain. First, the finely delineated structural information from ultra-high-field MRI can help us to identify accurate landmark structures, thereby making it easier to locate PET activation sites that are anatomically well-correlated with metabolic or ligand-specific organs in the neural structures in the brain. This synergistic potential of PET/MRI imaging is discussed in terms of neuroscience and neurological research from both translational and basic research perspectives. Experimental results from the hippocampus, thalamus, and brainstem obtained with ¹⁸F-fluorodeoxyglucose and ¹¹C-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)benzonitrile are used to demonstrate the potential of this new brain PET/MRI system.     

Parity induced edge-current saturation and current distribution in zigzag-edged graphene nano-ribbon devices

We show computationally that the current-voltage characteristics of the zigzag-edged graphene nanoribbon (ZGNR) with the even width exhibit remarkable current saturation behavior in spite of the absence of the bandgap. Mechanism of such current-saturation behavior can be understood to be originated from the symmetries of the wavefunctions corresponding to the edge states in ZGNR. We further demonstrate that the current-voltage characteristics of ZGNR can be drastically changed even by the presence of a single lattice vacancy, with the strong dependence on the position of the vacancy. The origin of such properties is intuitively understood by analyzing the transmission probabilities through such systems.     

In vitro formation and thermal transition of novel hybrid fibrils from type I fish scale collagen and type I porcine collagen

Novel type I collagen hybrid fibrils were fabricated by neutralizing a mixture of type I fish scale collagen solution and type I porcine collagen solution with a phosphate buffer saline at 28 °C. Their structure was discussed in terms of the volume ratio of fish/porcine collagen solution. Scanning electron and atomic force micrographs showed that the diameter of collagen fibrils derived from the collagen mixture was larger than those derived from each collagen, and all resultant fibrils exhibited a typical D-periodic unit of ∼67 nm, irrespective of volume ratio of both collagens. Differential scanning calorimetry revealed only one endothermic peak for the fibrils derived from collagen mixture or from each collagen solution, indicating that the resultant collagen fibrils were hybrids of type I fish scale collagen and type I porcine collagen.     

Decision methodology of end-milling conditions using data-mining

The purpose of the present study is to apply data-mining methods to support the decision of reasonable cutting conditions. Although an enormous amount of information is listed in a catalog, it is not possible to know all of it. Seen from the viewpoint of the user, this enormous amount of information becomes a hindrance. For example, even if an expert worker does not look at a catalog, in end-mill processing, he can decide the appropriate processing condition efficiently from experience; however, this type of situation creates difficult problems for an unskilled worker or a skilled worker with little experience. The recommended cutting condition for every type of material is listed in a catalog together with the appropriate tool, but it takes much time and labor to search and examine the catalog to find the right tool, and this process is inefficient. The main subject of our research was to support the processing condition of the end-mill for each precision tool efficiently based on end-mill clusters. Our research applied the techniques of data mining, in particular, non-hierarchy clustering and hierarchy clustering, to catalog data. With these techniques, we applied multiple regression analysis and reached the following main conclusions. As a first step, we paid attention to the shape element of catalog data. In addition to using conventional mining processes, we grouped end-mills from the viewpoint of tool shape, which meant the ratio of dimensions, visually by applying the K-means method. We applied variable cluster analysis next to each cluster and extracted an predictor variable to represent each cluster, and we performed multiple regression analysis and derived a cutting condition decision formula. The cutting condition decision formula provided high accuracy. The accuracy was higher than the results achieved through mining of all data. A more highly precise processing condition decision formula was derived by doing mining again, excluding the peculiar data clusters such as small diameter end-mill. We understood what was effective for cutting condition decision to be factors related to blade length and the ratio of the full length, factors which have not been singled out through background knowledge or expert knowledge, but were noticed as an effect of catalog mining.     

Combustion characteristics of a hydroxylammonium nitrate based liquid propellant. Combustion mechanism and application to thrusters

A new composition of hydroxylammonium nitrate based solution containing ammonium nitrate, methanol, and water was developed for monopropellant in a reaction control system (RCS) as an alternative to conventional hydrazine. In comparison with hydrazine, this solution has a 20% higher specific impulse, 1.4 times higher density, and lower freezing point and toxicity. The linear burning rate of the solution is moderate at the operating pressures of RCS thrusters. It was found that the linear burning rate had some characteristics whose mechanisms had not been understood. The combustion mechanism of this solution was investigated. The burning behavior was observed using a medium speed camera, and a temperature profile for the combustion wave was measured with a 2.5 μm diameter thermocouple. From these results, the instability of the liquid-gas interface may trigger a sudden increase in the burning rate, and methanol was found to be effective in reducing the bubble growth rate in the solution. The reactivity of several catalysts was evaluated in an open-cup test, and the S405 catalyst for hydrazine showed the best performance among them. Thruster tests were conducted using the S405 catalyst with variation in the propellant mass flow rate, catalyst bed configuration, and length-to-diameter ratio of the combustor. As a result, parameters were determined that ensured long operating time. The model thruster operated stably for up to 100 sec with a specific impulse I _sp = 240 sec, which corresponds to a 90% efficiency. __________ Translated from Fizika Goreniya i Vzryva, Vol. 45, No. 4, pp. 109–120, July–August, 2009. An erratum to this article can be found at     

On Robust Stability And Sensitivity Of Circadian Rhythms

We develop an approach to robustness analysis of circadian rhythms from the viewpoints of (local) robust stability of periodic trajectories and their period‐sensitivity, based on mathematical models. Our attention is directed to the core molecular model generating circadian rhythms in Drosophila, proposed by Goldbeter [1], for our approach to be illustrated. We consider two cases when the circadian rhythms are subjected to periodic forcing by light/dark (LD) cycles and when the circadian rhythms are under continuous darkness (DD). First, we propose conditions/algorithms for (local) robust stability, and show that the circadian rhythms generated by the core molecular model are (locally) robustly stable, in both LD and DD cases. Second, in DD case, we derive a formula of period sensitivity, and assess effects of (infinitesimal) parameter‐variations on the period of the circadian rhythms.     

Modulated Hebb-Oja learning Rule-a method for principal subspace analysis

This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view-synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method.     

Microcoaxial electrode for in vivo nitric oxide measurement

Nitric oxide (NO) is a gaseous mediator involved in various physiological phenomena, such as vasorelaxation and neurotransmission. Investigation of local cellular responses of NO production in vivo and in vitro requires a measurement method with a high spatial resolution. For selective NO measurement, we therefore developed a microcoaxial electrode whose tip diameter is less than 10 microm. Calibration using various concentrations of NO (0.1-1.0 microM) showed that the electrode has good linearity (r = 0.99) and its detection limit is 0.075 microM (S/N = 3). We verified the applicability of this electrode to in vivo and in vitro local measurement NO released from bovine aortic cultured endothelial cells (BAECs) stimulated by acetylcholine (ACh). After the addition of ACh, a transient increase in NO concentration was detected by the electrode. In the presence of NG-nitro-L-arginine methyl ester (L-NAME), a putative NO synthase inhibitor, NO release (peak NO concentration) from RAECs was significantly less than that in the absence of L-NAME (0.18 +/- 0.04 microM vs 0.47 +/- 0.13; P < 0.01). After removal of L-NAME, NO release partially recovered (0.39 +/- 0.10 microM). In conclusion, the microcoaxial electrode was successfully applied to direct and continuous NO measurement in biological systems.