Key Intrinsic Connectivity Networks for Individual Identification With Siamese Long Short-Term Memory

In functional magnetic resonance imaging (fMRI) analysis, many studies have been conducted on inter-subject variability as well as intra-subject reproducibility. These studies indicate that fMRI could have unique characteristics for individuals. In this study, we hypothesized that the dynamic information during 1 min of fMRI was unique and repetitive enough for each subject, so we applied long short-term memory (LSTM) using initial time points of dynamic resting-state fMRI for individual identification. Siamese network is used to obtain robust individual identification performance without additional learning on a new dataset. In particular, by adding a new structure called region of interest–wise average pooling (RAP), individual identification performance could be improved, and key intrinsic connectivity networks (ICNs) for individual identification were also identified. The average performance of individual identification was 97.88% using the test dataset in eightfold cross-validation analysis. Through the visualization of features learned by Siamese LSTM with RAP, ICNs spanning the parietal region were observed as the key ICNs in identifying individuals. These results suggest the key ICNs in fMRI could represent individual uniqueness

Fetal cortical plate segmentation using fully convolutional networks with multiple plane aggregation

Fetal magnetic resonance imaging (MRI) has the potential to advance our understanding of human brain development by providing quantitative information of cortical plate (CP) developmen

Optimal method for fetal brain age prediction using multiplanar slices from structural magnetic resonance imaging

The accurate prediction of fetal brain age using magnetic resonance imaging (MRI) may contribute to the identification of brain abnormalities and the risk of adverse developmental outcomes. This study aimed to propose a method for predicting fetal brain age using MRIs from 220 healthy fetuses between 15.9 and 38.7 weeks of gestational age (GA). We built a 2D single-channel convolutional neural network (CNN) with multiplanar MRI slices in different orthogonal planes without correction for interslice motion. In each fetus, multiple age predictions from different slices were generated, and the brain age was obtained using the mode that determined the most frequent value among the multiple predictions from the 2D single-channel CNN. We obtained a mean absolute error (MAE) of 0.125 weeks (0.875 days) between the GA and brain age across the fetuses. The use of multiplanar slices achieved significantly lower prediction error and its variance than the use of a single slice and a single MRI stack. Our 2D single-channel CNN with multiplanar slices yielded a significantly lower stack-wise MAE (0.304 weeks) than the 2D multi-channel (MAE = 0.979

All-Solid-State Lithium Battery Working without an Additional Separator in a Polymeric Electrolyte

Considering the safety issues of Li ion batteries, an all-solid-state polymer electrolyte has been one of the promising solutions. Achieving a Li ion conductivity of a solid-state electrolyte comparable to that of a liquid electrolyte (>1 mS/cm) is particularly challenging. Even with characteristic ion conductivity, employment of a polyethylene oxide (PEO) solid electrolyte has not been sufficient due to high crystallinity. In this study, hybrid solid electrolyte (HSE) systems have been designed with Li1.3Al0.3Ti0.7(PO4)3 (LATP), PEO and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). A hybrid solid cathode (HSC) is also designed using LATP, PEO and lithium cobalt oxide (LiCoO2, LCO)—lithium manganese oxide (LiMn2O4, LMO). The designed HSE system has 2.0 × 10−4 S/cm (23 °C) and 1.6 × 10−3 S/cm (55 °C) with a 6.0 V electrochemical stability without an additional separator membrane introduction. In these systems, succinonitrile (SN) has been incorporated as a plasticizer to reduce crystallinity of PEO for practical all-solid Li battery system development. The designed HSC/HSE/Li metal cell in this study operates without any leakage and short-circuits even under the broken cell condition. The designed HSC/HSE/Li metal cell in this study displays an initial charge capacity of 82/62 mAh/g (23 °C) and 123.4/102.7 mAh/g (55 °C). The developed system overcomes typical disadvantages of internal resistance induced by Ti ion reduction. This study contributes to a new technology development of all-solid-state Li battery for commercial product design

Structural Effects of Metal-free Catalysts in the Cathode of Membrane Electrode Assemblies for Alkaline Anion Exchange Membrane Fuel Cells

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An Avatar-Based Weather Forecast Sign Language System for the Hearing-Impaired

Part 12: Data Mining-ForecastingInternational audienceIn this paper, we describe a text-to-animation framework for TV weather forecast sign language presentation. To this end, we analyzed the last three years’ weather forecast scripts to obtain the frequency of each word and determine the order of motion capture. About 500 sign language words were chosen and motion-captured for the weather forecast purpose, in addition to the existing 2,700 motions prebuilt for daily life. Words that are absent in the sign language dictionary are replaced with synonyms registered in KorLex, the Korean Wordnet, to improve the translation performance. The weather forecast with sign language is serviced via the Internet in an on-demand manner and can be viewed by PC or mobile devices

Ostwald Ripening Driven Exfoliation to Ultrathin Layered Double Hydroxides Nanosheets for Enhanced Oxygen Evolution Reaction

As a key half-reaction in water splitting, the oxygen evolution reaction (OER) process is kinetically sluggish. Layered double hydroxides (LDHs) are regarded as the highly promising electrocatalysts to promote the OER kinetics. However, the closely stacking layered structure of pristine bulk LDHs restricts the exposure of electrocatalytically active sites, and it remains a great challenge to find an efficient strategy to exfoliate the bulk LDHs into ultrathin and stable nanosheets with increased surface area and exposed active sites. Herein, a novel Ostwald ripening driven exfoliation (ORDE) of NiFe LDHs has been achieved in situ on the electrodes by spontaneously self-etching and redepositing via a simple hydrothermal treatment without the assistance of any exfoliating reagent or surfactant. The thermodynamically driven Ostwald ripening has been expanded to the exfoliation of two-dimensional layered materials for the first time. Compared with conventional exfoliation methods, this ORDE is a time-saving and green strategy that avoids the serious adsorption of surfactant molecules. The ORDE of NiFe LDHs is accomplished in situ on a Cu mesh electrode, which not only exhibits excellent electrical contact between LDHs catalyst and electrodes but also prevents the restacking of the exfoliated LDHs. As a result, the exfoliated ultrathin, clean, and vertically aligned NiFe nanosheets with much higher surface area and numerous exposed active edges and sites demonstrated significantly enhanced OER performances with low overpotential of 292 mV at 10 mA cm(-2) and long-term stability for more than 60 h, as well as remarkable flexibility. Additionally, bulk Ni(OH)(2) nanosheets on Ni foams have also been exfoliated by a similar mechanism, indicating this ORDE strategy can be widely extended to other 2D layered materials for novel applications.11Nsciescopu