有限要素解析による管フランジ締結体の締付けおよび力学的特性の評価に関する研究

博士（工学）神戸大

Untangling perceptual memory: hysteresis and adaptation map into separate cortical networks

Perception is an active inferential process in which prior knowledge is combined with sensory input, the result of which determines the contents of awareness. Accordingly, previous experience is known to help the brain “decide” what to perceive. However, a critical aspect that has not been addressed is that previous experience can exert 2 opposing effects on perception: An attractive effect, sensitizing the brain to perceive the same again (hysteresis), or a repulsive effect, making it more likely to perceive something else (adaptation). We used functional magnetic resonance imaging and modeling to elucidate how the brain entertains these 2 opposing processes, and what determines the direction of such experience-dependent perceptual effects. We found that although affecting our perception concurrently, hysteresis and adaptation map into distinct cortical networks: a widespread network of higher-order visual and fronto-parietal areas was involved in perceptual stabilization, while adaptation was confined to early visual areas. This areal and hierarchical segregation may explain how the brain maintains the balance between exploiting redundancies and staying sensitive to new information. We provide a Bayesian model that accounts for the coexistence of hysteresis and adaptation by separating their causes into 2 distinct terms: Hysteresis alters the prior, whereas adaptation changes the sensory evidence (the likelihood function)

SORN: A Self-Organizing Recurrent Neural Network

Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artificial neural network models. Here we introduce SORN, a self-organizing recurrent network. It combines three distinct forms of local plasticity to learn spatio-temporal patterns in its input while maintaining its dynamics in a healthy regime suitable for learning. The SORN learns to encode information in the form of trajectories through its high-dimensional state space reminiscent of recent biological findings on cortical coding. All three forms of plasticity are shown to be essential for the network's success

Influence of Mahaleb and Gisela 5 Rootstocks on the Growth of „Bigarreau Burlat†Sweet Cherry Cultivar

Abstract. The influence of Prunus Mahaleb L. and ‘Gisela 5’ rootstocks on the growth of ‘Biggareau Burlat’ sweet cherry cultivar was evaluate on the environmental conditions of Cluj-Napoca city, in 2015, in a high-density plot (trees are planted at the distance of 4 x 1.5 m) with 1666 trees/ha, trained as spindle busch, with trellis system and drip fert-irigation provided. The measurements were done in April, on 10 trees of the cultivar grafted on different rootstock, in the 4th year after planting. The trunck diameter growth was measured 5 cm above the graft, and it was also recorded the number and length of annual increases (long, medium and spur fruiting branches) and calculated the tree height. After first four years from planting, ‘Biggareau Burlat’ grafted on ‘Gisela 5’ rootstock proved to be more vigorously than grafted on Prunus Mahaleb L., considering the total numbers of the medium and long branches per tree. ‘Biggareau Burlat’/Gisela 5, compared to ‘Biggareau Burlat’/P. Mahaleb significantly exceeded in the number of medium branches (4.7 comparatively to 3), number of long branches on the tree (17.2 comparatively to 7.9), number of inflorescences buds (74.7 comparatively to 41.3)  and the total length of annual tree branches

Untangling Perceptual Memory: Hysteresis and Adaptation Map into Separate Cortical Networks

Perception is an active inferential process in which prior knowledge is combined with sensory input, the result of which determines the contents of awareness. Accordingly, previous experience is known to help the brain "decide” what to perceive. However, a critical aspect that has not been addressed is that previous experience can exert 2 opposing effects on perception: An attractive effect, sensitizing the brain to perceive the same again (hysteresis), or a repulsive effect, making it more likely to perceive something else (adaptation). We used functional magnetic resonance imaging and modeling to elucidate how the brain entertains these 2 opposing processes, and what determines the direction of such experience-dependent perceptual effects. We found that although affecting our perception concurrently, hysteresis and adaptation map into distinct cortical networks: a widespread network of higher-order visual and fronto-parietal areas was involved in perceptual stabilization, while adaptation was confined to early visual areas. This areal and hierarchical segregation may explain how the brain maintains the balance between exploiting redundancies and staying sensitive to new information. We provide a Bayesian model that accounts for the coexistence of hysteresis and adaptation by separating their causes into 2 distinct terms: Hysteresis alters the prior, whereas adaptation changes the sensory evidence (the likelihood function

Activated carbons with extremely high surface area produced from cones, bark and wood using the same procedure

Activated carbons have been previously produced from a huge variety of biomaterials often reporting advantages of using certain precursors. Here we used pine cones, spruce cones, larch cones and a pine bark/wood chip mixture to produce activated carbons in order to verify the influence of the precursor on properties of the final materials. The biochars were converted into activated carbons with extremely high BET surface area up to similar to 3500 m(2) g(-1) (among the highest reported) using identical carbonization and KOH activation procedures. The activated carbons produced from all precursors demonstrated similar specific surface area (SSA), pore size distribution and performance to electrodes in supercapacitors. Activated carbons produced from wood waste appeared to be also very similar to "activated graphene" prepared by the same KOH procedure. Hydrogen sorption of AC follows expected uptake vs. SSA trends and energy storage parameters of supercapacitor electrodes prepared from AC are very similar for all tested precursors. It can be concluded that the type of precursor (biomaterial or reduced graphene oxide) has smaller importance for producing high surface area activated carbons compared to details of carbonization and activation. Nearly all kinds of wood waste provided by the forest industry can possibly be converted into high quality AC suitable for preparation of electrode materials