Noninvasive prediction of shunt operation outcome in idiopathic normal pressure hydrocephalus

Idiopathic normal pressure hydrocephalus (iNPH) is a syndrome characterized by gait disturbance, cognitive deterioration and urinary incontinence in elderly individuals. These symptoms can be improved by shunt operation in some but not all patients. Therefore, discovering predictive factors for the surgical outcome is of great clinical importance. We used normalized power variance (NPV) of electroencephalography (EEG) waves, a sensitive measure of the instability of cortical electrical activity, and found significantly higher NPV in beta frequency band at the right fronto-temporo-occipital electrodes (Fp2, T4 and O2) in shunt responders compared to non-responders. By utilizing these differences, we were able to correctly identify responders and non-responders to shunt operation with a positive predictive value of 80% and a negative predictive value of 88%. Our findings indicate that NPV can be useful in noninvasively predicting the clinical outcome of shunt operation in patients with iNPH

Social robot for older adults with cognitive decline: a preliminary trial

The number of older adults living alone is rapidly increasing. Loneliness in older adults not only degrade their quality of life but also causes troubles such as heavy burden on the medical staff, especially when cognitive decline is present. Social robots could be used in several ways to reduce such problems. As a first step towards this goal, we introduced conversation robots into the homes of older adults with cognitive decline to evaluate the robot’s availability and acceptance during several months. The study involved two steps, one for evaluating the robustness of the proposed robotic system, and the second one to examine the long-term acceptance of social robots by older adults with cognitive decline living alone. Our data shows that after several weeks of human-robot interaction, the participants continued to use the robot and successfully integrated them into their lives. These results open the possibility of further research involving how sustained interaction can be achieved, as well as which factors contributed to the acceptance of the robot

Energy transfer dynamics in wire-type dendrimers having oligophenylene peripheries

Energy transfer and shielding effect are studied in wire-type dendrimers (GnPPV: n-th generation dendrimer with poly(p-phenylenevinylene) backbone; n = 1, 2) having oligophenylene light-harvesting (LH) antenna. Following the excitation of the LH-antennae, backbone-polymers in GnPPV give rise to intense photoluminescence (PL) bands. This is due to the presence of highly efficient energy transfer from the LH-antennae to the backbone-polymers. The intensity of backbone-PL increases faster than the decay of the antenna-PL. This result indicates that rapid energy-transfer from antenna to backbone takes place utilizing the overlap of wavefunctions in the excited states. In G2PPV having larger LH-antenna, shielding effect against inter-backbone interactions is recognized more effectively than G1PPV. In solid films of GnPPV, red shifts of the backbone-PL bands are observed. This is caused by inter-backbone interactions of the wire-type dendrimers due to aggregation. The extent of the red shift in G2PPV is smaller than that of G1PPV. This result suggests that the larger LH-antenna in G2PPV substantially wraps its backbone-polymer and shields the inter-backbone interactions

Deep learning-based bubble detection with automatic training data generation: Application to the PEM water electrolysis

Various fields, such as the paper industry, chemical engineering, and renewable energy, are faced with gas-liquid two-phase flows and are being studied by visualization and observation. Although it is necessary to quantitatively evaluate the characteristics of bubbles, there is a limitation in the amount of labor required for detection and measurement by human observation of images. There are no examples for bubbles in polymer electrolyte membrane water electrolysis (PEMWE), where the bubbles in PEMWE have heterogeneous backgrounds, unpatterned patterns, and unclear bubble contours. Existing methods for detecting these bubbles are not expected to be accurate enough. In this study, a deep learning-based bubble detection method using convolutional neural networks (CNN) was developed for bubbles in PEMWE. Our method has two novel approaches: first, we developed an algorithm that automatically draws a pseudo-bubble image based on an actual bubble image on an arbitrary background as a method for automatically generating training data for the CNNs. Second, we developed a CNN-based bubble detection method that uses the motion of bubbles, specifically, the difference between the bubble image and the image from one frame ago, as input. Finally, we tested the algorithm on bubble images in a PEMWE and achieved an F1 score of 0.83 or better for all current densities of 0.5, 1, 2, and 3 A/cm2, and an F1 score of 0.844 for the entire detection

Association between Bone-Related Physiological Substances and Oral Function in Community-Dwelling Older People

Background: Oral dysfunction is related to long-term cares including activities of daily living. The objective of this study was to determine the association between oral function and the bone-related physiological substances osteocalcin (OC) and insulin-like growth factor-1 (IGF-1). Methods: The study participants were 139 community-dwelling older people in Japan. Evaluation of oral dysfunction was based on subjective judgment by each participant. Blood analysis included OC, IGF-1, and albumin. Results: Univariate and multiple logistic analyses showed that IGF-1 was significantly associated with a “decline in masticatory function” (p = 0.0074 and p = 0.0308, respectively). Receiver operating characteristic curve analysis of IGF-1 levels revealed a threshold score of 108 ng/mL (p < 0.01) for discriminating a “decline in masticatory function”. Logistic regression analysis revealed that participants with an IGF-1 level ≤108 ng/mL had an odds ratio of 4.31 (p < 0.05) for a “decline in masticatory function”. No significant association was found between the OC level and oral dysfunction. Conclusions: These results suggest a possible relationship between lower serum IGF-1 levels and a decline in masticatory dysfunction in community-dwelling older people