Brain-mediated Transfer Learning of Convolutional Neural Networks

The human brain can effectively learn a new task from a small number of samples, which indicate that the brain can transfer its prior knowledge to solve tasks in different domains. This function is analogous to transfer learning (TL) in the field of machine learning. TL uses a well-trained feature space in a specific task domain to improve performance in new tasks with insufficient training data. TL with rich feature representations, such as features of convolutional neural networks (CNNs), shows high generalization ability across different task domains. However, such TL is still insufficient in making machine learning attain generalization ability comparable to that of the human brain. To examine if the internal representation of the brain could be used to achieve more efficient TL, we introduce a method for TL mediated by human brains. Our method transforms feature representations of audiovisual inputs in CNNs into those in activation patterns of individual brains via their association learned ahead using measured brain responses. Then, to estimate labels reflecting human cognition and behavior induced by the audiovisual inputs, the transformed representations are used for TL. We demonstrate that our brain-mediated TL (BTL) shows higher performance in the label estimation than the standard TL. In addition, we illustrate that the estimations mediated by different brains vary from brain to brain, and the variability reflects the individual variability in perception. Thus, our BTL provides a framework to improve the generalization ability of machine-learning feature representations and enable machine learning to estimate human-like cognition and behavior, including individual variability

THE KNEE AND HIP JOINT ANGLE WHEN ILIOTIBIAL BAND SLIDE OVER THE LATERAL FEMORAL EPICONDYLE

According to a previous study, the knee flexion angle, is approximately 30°when the iliotibial band (ITB) slides over the lateral femoral epicondyle. However, the corresponding hip joint flexion angle has not yet been determined. The purpose of this study was to examine whether hip joint flexion angle affects the location of the ITB. The study included 16 uninjured male subjects. The subjects had their knee flexion angle measured when the ITB slides over the lateral femoral epicondyle at five different hip joint angles: 10° of extension and 0°, 20°, 40°, 60° of flexion. As the hip joint flexion angle increased, the knee flexion angle also increased. It should be considered that the position of the ITB affects the knee joint angle, as well as the hip joint angle. The findings of this study may help improve the treatment and prevention of ITB friction syndrome

The Th17/IL-23 Axis and Natural Immunity in Psoriatic Arthritis

Psoriatic arthritis (PsA) is a chronic inflammatory skin disease that causes enthesitis and destructive arthritis and significantly lowers patient quality of life. Recognition of the two target organs (the skin and joints) involved in the immunopathophysiology of PsA helped in elucidating the pathology of various systemic autoimmune diseases targeting multiple organs. Recent advances in immunology and genetics have made it clear that acquired immunity, especially that mediated by the Th17/IL-23 axis, plays an important role in the inflammatory pathology observed in psoriasis and PsA. Additionally, involvement of natural immunity has also been suggested. Microbial infection has been known to trigger psoriasis and PsA. Recent clinical studies using biopharmaceuticals, such as tumor-necrosis-factor- (TNF-) α inhibitors and IL-12/23 p40 antibodies, indicate that studies need not be based only on the immunological phenomena observed in PsA pathology since disease pathology can now be verified using human-based science. Considering this aspect, this paper discusses the immunopathology of PsA compared to psoriasis (cutaneous) and rheumatoid arthritis in humans and immunopathology of PsA with respect to the Th17/IL-23 axis and microbial infection

Flow-induced hardening of endothelial nucleus as an intracellular stress-bearing organelle

The mechanical contribution of nucleus in adherent cells to bearing intracellular stresses remains unclear. In this paper, the effects of fluid shear stress on morphology and elastic properties of endothelial nuclei were investigated. The morphological observation suggested that the nuclei in the cytoplasm were being vertically compressed under static conditions, whereas they were elongated and more compressed with a fluid shear stress of 2 Pa (20 dyn/cm(2)) onto the cell. The elongated nuclei remained the shape even after they were isolated from the cells. The micropipette aspiration technique on the isolated nuclei revealed that the elastic modulus of elongated nuclei, 0.62 +/- 0.15 kPa (n = 13, mean +/- SD), was significantly higher than that of control nuclei, 0.42 +/- 0.12 kPa (n = 11), suggesting that the nuclei remodeled their structure due to the shear stress. Based of these results and a transmission electron microscopy, a possibility of the nucleus as an intracellular compression-bearing organelle was proposed, which will impact interpretation of stress distribution in adherent cells. (C) 2005 Elsevier Ltd. All rights reserved

Relational Network of People Constructed on the Basis of Similarity of Brain Activities.

The relational network of people (RNP) model has been attracting the interest of not only researchers but also industrial engineers. RNP can be constructed from friend lists in online social networking services (SNSs) and from inter-contact logs between individuals. One of the killer applications of RNP is the prediction of user demands, which is key to maximizing user satisfaction in content delivery services such as video streaming and video advertising. It is well known that an RNP representing social closeness between individuals (a so-called social network) can estimate user preferences simply, as we expect that people close to each other will have similar preferences. However, although there are many metrics that enable the social closeness between individuals to be measured, it is unclear which metric is best suited for individual services. Therefore, this paper introduces a new approach based on brain imaging. Brain imaging using functional Magnetic Resonance Imaging (fMRI) is powerful because it enables us to directly observe how a video content stimulates the brains of individual people. We propose a brain imaging-based RNP that represents the similarity of video-evoked brain activities between people as a network graph. We show an application scenario featuring predictive content delivery using the proposed RNP in which, when a user shows interest in a video content in some way, other users close to him or her can be expected to also be interested in it because their brain activities are correlated. Through numerical evaluation using multiple real datasets obtained by fMRI, we demonstrate that the proposed RNP is generalizable across brain imaging results for different sets of video content, thus suggesting that brain imaging data can be used to robustly generate RNP for utilization as a powerful tool for estimating user preferences

Gravitational collapse and formation of a black hole in a type II minimally modified gravity theory

We study the spherically symmetric collapse of a cloud of dust in VCDM, a class of gravitational theories with two local physical degrees of freedom. We find that the collapse corresponds to a particular foliation of the Oppenheimer-Snyder solution in general relativity (GR) which is endowed with a constant trace for the extrinsic curvature relative to the time $t$ constant foliation. For this solution, we find that the final state of the collapse leads to a static configuration with the lapse function vanishing at a radius inside the apparent horizon. Such a point is reached in an infinite time-$t$ interval, $t$ being the cosmological time, i.e. the time of an observer located far away from the collapsing cloud. The presence of this vanishing lapse endpoint implies the necessity of a UV completion to describe the physics inside the resulting black hole. On the other hand, since the corresponding cosmic time $t$ is infinite, VCDM can safely describe the whole history of the universe at large scales without knowledge of the unknown UV completion, despite the presence of the so-called shadowy mode.Comment: 22 pages, 9 figure