Tool-Use Model to Reproduce the Goal Situations Considering Relationship Among Tools, Objects, Actions and Effects Using Multimodal Deep Neural Networks

We propose a tool-use model that enables a robot to act toward a provided goal. It is important to consider features of the four factors; tools, objects actions, and effects at the same time because they are related to each other and one factor can influence the others. The tool-use model is constructed with deep neural networks (DNNs) using multimodal sensorimotor data; image, force, and joint angle information. To allow the robot to learn tool-use, we collect training data by controlling the robot to perform various object operations using several tools with multiple actions that leads different effects. Then the tool-use model is thereby trained and learns sensorimotor coordination and acquires relationships among tools, objects, actions and effects in its latent space. We can give the robot a task goal by providing an image showing the target placement and orientation of the object. Using the goal image with the tool-use model, the robot detects the features of tools and objects, and determines how to act to reproduce the target effects automatically. Then the robot generates actions adjusting to the real time situations even though the tools and objects are unknown and more complicated than trained ones

Distribution of Uranium in the Indian and the Soutbern Ocean Waters

The content of uranium was determined for sea water samples collected on board M. S. SOYA on her cruises from Japan to Antarctica during the fifth and sixth Japanese Antarctic Research Expeditions (1960-61,1961-62) and in the Drake Passage on board S. S. CAPITAN CANEPA of the Argentine Navy Hydrographic Service during the TRIDENTE-3 cruise (Feb.-Mar., 1963). Uranium was analyzed by the fluorometric method using transmission type fluorometer after separation by solvent extraction and fusion with sodium fluoride. The analytical results showed that the uranium content in surface water respectively ranged from 2.7 to 3.2×10^g/l in the Indian Ocean Basin of the Antaratic, Ocean, 2.7 to 3.5×10^g/l in the Drake Passage, 2.5 to 3.5×10^g/l in the Indian Ocean and 2.5 to 3.3×10^g/l in the South China Sea. Judging from the mean value of 0.5×10^g/l for radium in the Indian Ocean (PETTERSSON, 1955; KOCZY and SZABO, 1962) the ratio of radium to uranium may be 4 to 6 per cent of the secular equilibrium amount

Moiré superlattice and two-dimensional free-electron-like states of indium triple-layer structure on Si(111)

We studied the growth of an indium triple-atomic-layer film and the two-dimensional free-electron-like electronic states on Si(111) by low-energy electron diffraction (LEED), scanning tunneling microscopy (STM), and angle-resolved photoelectron spectroscopy (ARPES). By depositing In on the In/Si(111)- √ 7 × √ 3-rect surface below 100 K, followed by brief postannealing up to 140 K, we successfully obtained well-crystalline films exhibiting sharp superstructure LEED spots. We revealed an (11 × 11) superlattice of the triple-layer structure, while both LEED and STM showed a (5.5 × 5.5) pseudoperiodicity. This pseudoperiodicity was attributed to the moiré interference between the Si(111)-(11 × 11) lattice (a = 3.84 Å) and the In (13 × 13) hexagonal lattice, which has a lattice constant of 3.25 Å, with the ratio very close to 13/11. ARPES measurements unveiled two free-electron-like states with Fermi wave vectors of 1.32 and 1.46 Å⁻¹. We also observed replica Fermi surfaces, which are associated with the reciprocal lattice vectors of both the (1 × 1) Si(111) and the In hexagonal layers. This further confirms the hexagonal atomic arrangement of the In triple-layer structure

1α,25-Dihydroxyvitamin D3 enhances cerebral clearance of human amyloid-β peptide(1-40) from mouse brain across the blood-brain barrier

<p>Abstract</p> <p>Background</p> <p>Cerebrovascular dysfunction has been considered to cause impairment of cerebral amyloid-β peptide (Aβ) clearance across the blood-brain barrier (BBB). Further, low levels of vitamin D are associated with increased risk of Alzheimer's disease, as well as vascular dysfunction. The purpose of the present study was to investigate the effect of 1α,25-dihydroxyvitamin D₃(1,25(OH)₂D3), an active form of vitamin D, on cerebral Aβ clearance from mouse brain.</p> <p>Methods</p> <p>The elimination of [¹²⁵I]hAβ(1-40) from mouse brain was examined by using the Brain Efflux Index method to determine the remaining amount of [¹²⁵I]hAβ(1-40) radioactivity after injection into the cerebral cortex. [¹²⁵I]hAβ(1-40) internalization was analyzed using conditionally immortalized mouse brain capillary endothelial cells (TM-BBB4).</p> <p>Results</p> <p>Twenty-four hours after intraperitoneal injection of 1,25(OH)₂D3 (1 μg/mouse), [¹²⁵I]hAβ(1-40) elimination from mouse brain was increased 1.3-fold, and the level of endogenous Aβ(1-40) in mouse brain was reduced. These effects were observed at 24 h after i.p. injection of 1,25(OH)₂D3, while no significant effect was observed at 48 or 72 h. Vitamin D receptor (VDR) mRNA was detected in mouse brain capillaries, suggesting that 1,25(OH)₂D3 has a VDR-mediated genomic action. Furthermore, forskolin, which activates mitogen-activated protein kinase kinase (MEK), enhanced [¹²⁵I]hAβ(1-40) elimination from mouse brain. Forskolin also enhanced [¹²⁵I]hAβ(1-40) internalization in TM-BBB4 cells, and this enhancement was inhibited by a MEK inhibitor, suggesting involvement of non-genomic action.</p> <p>Conclusions</p> <p>The active form of vitamin D, 1,25(OH)₂D3, appears to enhance brain-to-blood Aβ(1-40) efflux transport at the BBB through both genomic and non-genomic actions. Compounds activating these pathways may be candidate agents for modulating Aβ(1-40) elimination at the BBB.</p

A Neurorobotics Simulation of Autistic Behavior Induced by Unusual Sensory Precision

Recently, applying computational models developed in cognitive science to psychiatric disorders has been recognized as an essential approach for understanding cognitive mechanisms underlying psychiatric symptoms. Autism spectrum disorder is a neurodevelopmental disorder that is hypothesized to affect information processes in the brain involving the estimation of sensory precision (uncertainty), but the mechanism by which observed symptoms are generated from such abnormalities has not been thoroughly investigated. Using a humanoid robot controlled by a neural network using a precision-weighted prediction error minimization mechanism, it is suggested that both increased and decreased sensory precision could induce the behavioral rigidity characterized by resistance to change that is characteristic of autistic behavior. Specifically, decreased sensory precision caused any error signals to be disregarded, leading to invariability of the robot’s intention, while increased sensory precision caused an excessive response to error signals, leading to fluctuations and subsequent fixation of intention. The results may provide a system-level explanation of mechanisms underlying different types of behavioral rigidity in autism spectrum and other psychiatric disorders. In addition, our findings suggest that symptoms caused by decreased and increased sensory precision could be distinguishable by examining the internal experience of patients and neural activity coding prediction error signals in the biological brain