The problem of reconstructing large-scale, gene regulatory networks from gene expression data has garnered considerable attention in bioinformatics over the past decade with the graphical modeling paradigm having emerged as a popular framework for inference. Analysis in a full Bayesian setting is contingent upon the assignment of a so-called structure prior—a probability distribution on networks, encoding a priori biological knowledge either in the form of supplemental data or high-level topological features. A key topological consideration is that a wide range of cellular networks are approximately scale-free, meaning that the fraction, , of nodes in a network with degree is roughly described by a power-law with exponent between and . The standard practice, however, is to utilize a random structure prior, which favors networks with binomially distributed degree distributions. In this paper, we introduce a scale-free structure prior for graphical models based on the formula for the probability of a network under a simple scale-free network model. Unlike the random structure prior, its scale-free counterpart requires a node labeling as a parameter. In order to use this prior for large-scale network inference, we design a novel Metropolis-Hastings sampler for graphical models that includes a node labeling as a state space variable. In a simulation study, we demonstrate that the scale-free structure prior outperforms the random structure prior at recovering scale-free networks while at the same time retains the ability to recover random networks. We then estimate a gene association network from gene expression data taken from a breast cancer tumor study, showing that scale-free structure prior recovers hubs, including the previously unknown hub SLC39A6, which is a zinc transporter that has been implicated with the spread of breast cancer to the lymph nodes. Our analysis of the breast cancer expression data underscores the value of the scale-free structure prior as an instrument to aid in the identification of candidate hub genes with the potential to direct the hypotheses of molecular biologists, and thus drive future experiments.

A novel frequency response (FR) method is proposed: (i) Partial pressure(s) of reactant(s) in a steady-flow reactor is perturbed sinusoidally by varying gas space of the reactor with a definite angular frequency ω; (ii) amplitude and phase shift of every partial-pressure variation of both reactant(s) and product(s) is measured over a wide range of ω; (iii) on the other hand, characteristic functions of ω to explain "reaction-rate spectra" obtained from the data in (ii) are deduced analytically on the basis of a reaction mechanism; and (iv) complex rate coefficients, (k + iωl), involved in the functions are determined by numerical simulation to the spectra. The FR method is applied to CO oxidation over Ru/Al 2 O 3 at ca. 10 2 Pa and 623 K in order to confirm its efficiency: (i) As many as thirteen rate coefficients at five elementary steps were determined; (ii) chemical potentials of surface-intermediates, CO(a), O 2 (a), and O(a), were derived from l's; and (iii) free-energy dissipations via the three intermediates were deduced from chemical potential changes at five elementary steps. It is concluded that the reaction sequence of carbon monoxide, CO(g) f CO(a) f CO 2 (g), could occur spontaneously but the other sequence of oxygen, 1 / 2 O 2 (g) f 1 / 2 O 2 (a) f O(a) f CO 2 (g), would be against the reaction, although they are coupled.

CO 2 cascade heat pump system has been developed to realize an ultra-low temperature below the triple point of 0.518 MPa and − 56.6 C or less by flowing dry ice solid-gas state of CO 2 in a refrigeration system. Solid CO 2 in the refrigeration system may cause to block the flow in the evaporation process and make the system operation failed. To overcome the blocking phenomena and farther challenging lower refrigeration temperature, the CO 2 cyclone separator was newly proposed instead of the conventional evaporator for ultra-low temperature energy storage. The basic characteristics of CO 2 dry ice cycle separator were investigated by constructing test rigs and visual experiments. The visualization tests were carried out by three type separators: nonswirling type separator, cylindrical, and conical type cyclone separators. The results of visualization test showed that the size of the dry ice particles gets bigger by coalescing together with the strong swirling flow in the cyclone separator. In comparison with three type separators, particularly by using the conical type cyclone separator, the amount of accumulation of dry ice at the bottom of the separator was increased as a result of the growth in dry ice particle size.

The dry ice sublimation process of carbon dioxide (CO2) is a unique, environmentally friendly technology that can achieve a temperature of −56 °C or lower, which is a triple point of CO2 in CO2 refrigeration systems. In this study, a cyclone separator-evaporator was proposed to separate dry ice particles in an evaporator. As an initial step before introducing the cyclone separator-evaporator into an actual refrigeration system, a prototype cyclone separator-evaporator was constructed to visualize dry ice particles in a separation chamber. A high-speed camera was used to visualize the non-uniform flow of dry ice particles that repeatedly coalescence and collision in a swirl section. Consequently, the dry ice particle size and the circumferential and axial velocities of dry ice were measured. The results show that the equivalent diameter of the most abundant dry ice particles in the cyclone separation chamber is 2.0 mm. As the inner diameter of the separation section decreases, dry ice particles coalesce and grow from an equivalent diameter of 4 mm to a maximum of 40 mm. In addition, the comparison of the experimental and simulation results shows that the drag force due to CO2 gas flow is dominant in the circumferential velocity of dry ice particles.

This paper describes an automatic map vectortzation method to obtain geogmphical data from paper maps, for DB-systems using map information, like a GIs. The method consists of component sepamtion, and skeleton vectorization. To obtain accurate vector data, seveml special segmentation techniques and a new skeleton vectorization technique are introduced in the method. The segmentation techniques are used to extract line drawings, character symbols, and other components, such as painted objects, from the original map image. The new skeleton vectorization technique involves a shape reforming process to reform vector shape distortion cawed by raster-to-vector conversion. The process is based on the energy minimization principle. The process has an advantage in regard to reducing the various kinds of distortions, compared with wing conventional processes. Through map input experiments with the method, it was proved that the method can obtain accurate vector data, compared with conventional techniques.