TiO 2 thin films with high dielectric constants (83–100) were grown on a Ru electrode at a growth temperature of 250 °C using the atomic-layer deposition method. The as-deposited films were crystallized with rutile structure. Adoption of O3 with a very high concentration (400g∕m3) was crucial for obtaining the rutile phase and the high dielectric constant. The leakage current density of a TiO2 film with an equivalent oxide thickness of 1.0–1.5 nm was 10−6–10−8A∕cm2 at ±1V. All these electrical properties were obtained after limited postannealing where the annealing temperature was <500°C, which is crucial to the structural stability of the Ru electrode. Therefore, these TiO2 films are very promising as the capacitor dielectrics of dynamic random access memories. TiO2 films grown on a bare Si wafer or Pt electrode by the same process had anatase structure and a dielectric constant of ∼40.

Question-answering (QA) on video contents is a significant challenge for achieving human-level intelligence as it involves both vision and language in real-world settings. Here we demonstrate the possibility of an AI agent performing video story QA by learning from a large amount of cartoon videos. We develop a video-story learning model, i.e. Deep Embedded Memory Networks (DEMN), to reconstruct stories from a joint scene-dialogue video stream using a latent embedding space of observed data. The video stories are stored in a long-term memory component. For a given question, an LSTM-based attention model uses the long-term memory to recall the best question-story-answer triplet by focusing on specific words containing key information. We trained the DEMN on a novel QA dataset of children's cartoon video series, Pororo. The dataset contains 16,066 scene-dialogue pairs of 20.5-hour videos, 27,328 fine-grained sentences for scene description, and 8,913 story-related QA pairs. Our experimental results show that the DEMN outperforms other QA models. This is mainly due to 1) the reconstruction of video stories in a scene-dialogue combined form that utilize the latent embedding and 2) attention. DEMN also achieved state-of-the-art results on the MovieQA benchmark.

Greenhouse gases (GHGs) trapped in ice wedges may provide useful information on biogeochemical environments in ground ice. Previous studies have reported highly elevated CO 2 and CH 4 mixing ratios in ice wedges. However, N 2 O mixing ratios in ice wedges remain unknown. Here, we present CO 2 , CH 4 and N 2 O mixing ratios in bubbles and plausible mechanisms of GHG formation for two lakeside ice wedges at Cyuie village near Yakutsk. The CO 2 gas age corresponds to the Last Glacial Maximum (18-19 ka). The δ(N 2 /Ar) values and bubble shapes indicate that the ice wedges formed by dry snow compaction rather than snowmelt water refreezing, while the δ 18 O and δD values of the ice indicate changes in the source area location and/or the climate during the Last Glacial Maximum. Using a dry extraction method, we obtained gas mixing ratios of 7-13% CO 2 , 5-130 ppm CH 4 and 100-5000 ppb N 2 O. The δ(O 2 /Ar) values imply that most of the O 2 was consumed by biological respiration. The CH 4 is negatively correlated with N 2 O and CO 2 . The N 2 O might have inhibited CH 4 production.

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Liquid-crystalline (LC) hybrid polymers with functionalized silsesquioxanes with various proportions of LC monomer were synthesized by the reaction of polyhedral oligomeric silsesquioxane (POSS) macromonomer with methacrylate monomer having an LC moiety under common free-radical conditions. The obtained LC hybrid polymers were soluble in common solvents such as tetrahydrofuran, toluene, and chloroform, and their structures were characterized with Fourier transform infrared, 1 H NMR, and 29 Si NMR. The thermal stability of the hybrid polymers was increased with an increasing ratio of POSS moieties as the inorganic part. Because of the steric hindrance caused by the bulkiness of the POSS macromonomer, the numberaverage molecular weight of the hybrid polymers gradually decreased as the molar percentage of POSS in the feed increased. Their liquid crystallinities were very dependent on the POSS segments of the hybrid polymers behaving as hard, compact components. The hybrid polymer with 90 mol % LC moiety (Cube-LC90) showed liquid crystallinity, larger glass-transition temperatures, and better stability with respect to the LC homopolymer. The results of differential scanning calorimetry and optical polarizing microscopy showed that Cube-LC90 had a smectic-mesophase-like finegrained texture.

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