Preparation and Microstructure of Machinable Al\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e/Mica Composite by Ball Milling and Hot-Press Sintering

A machinable α-Al2O3/mica composite was prepared by hot-press sintering. In this experiment, a mica-contained glass ceramic in the MgO-Al2O3-SiO2-F glassy system was employed and the base glass powders were obtained by traditional melting-quenched method. Then, α-Al2O3 milling swarf was introduced by medium α-alumina milling ball to the glass powders. The test results indicate that the composites consist of mica crystal and mullite crystal, which are precipitated in the base glass. The α-Al2O3 shows an irregular polygon, which is inlayed in the base material. With the decrease of size of the base glass powders, the boundaries of composites among the sintered powders gradually vanish. The mica crystals in the composite also show an interlocking characteristic, which is a prerequisite of mica-contained glass ceramics with good machinability. Under different pressures, the tendency of preferred orientation is decreased with the reduction in grain size of glass powders, and the microstructure is proved to be consistent, significantly decreasing the composite’s hardness. Therefore, the machinability of the composite is improved

Moving Deep Learning into Web Browser: How Far Can We Go?

Recently, several JavaScript-based deep learning frameworks have emerged, making it possible to perform deep learning tasks directly in browsers. However, little is known on what and how well we can do with these frameworks for deep learning in browsers. To bridge the knowledge gap, in this paper, we conduct the first empirical study of deep learning in browsers. We survey 7 most popular JavaScript-based deep learning frameworks, investigating to what extent deep learning tasks have been supported in browsers so far. Then we measure the performance of different frameworks when running different deep learning tasks. Finally, we dig out the performance gap between deep learning in browsers and on native platforms by comparing the performance of TensorFlow.js and TensorFlow in Python. Our findings could help application developers, deep-learning framework vendors and browser vendors to improve the efficiency of deep learning in browsers

マウスおよびサルモデルを用いた野兎病菌 Francisella tularensis ΔpdpC変異株の弱毒生ワクチンとしての有用性の評価

学位の種別: 課程博士審査委員会委員 : （主査）東京大学准教授 平山 和宏, 東京大学教授 久和 茂, 東京大学教授 堀本 泰介, 東京大学准教授 芳賀 猛, 国立感染症研究所獣医学部部長 森川 茂University of Tokyo(東京大学

Seroprevalence of <em>Lawsonia intracellularis</em> antibodies in intensive pig farms in China

BACKGROUND: Porcine proliferative enteropathy caused by Lawsonia intracellularis (L. intracellularis) is a major concern to the pig industry worldwide. Although 8.3 billion pigs are produced each year in China, few reports on the prevalence of L.intracellularis infection are available. The aim of the current study was to estimate the seroprevalence of L. intracellularis antibodies in intensive pig farms in China. RESULTS: A total of 1060 serum samples were collected from 14 commercial pig farms located throughout China. Animals from all age groups were sampled including pre-weaning piglets, weaners, fattening pigs, adult sows and boars. Antibodies against L. intracellularis were detected using a specific blocking ELISA. Of the 1060 serum samples, 602 were identified as positive using the ELISA test. The apparent seroprevalence of L. intracellularis seropositivity was 57% (95% CI 50 to 64%). The true prevalence (that is, prevalence corrected for the imperfect sensitivity and specificity of the testing method) was 77% (95% CI 70 to 83%). CONCLUSIONS: The highest true prevalence was observed in sows and boars, suggesting that within a herd these stock classes are a reservoir for infection. The prevalence of L. intracellularis seropositivity in local breed pigs was significantly less than that in imported breeds. A higher seroprevalence was found in pigs in herds in Central and Northern China, which may correspond to the greater use of the intensive production systems in these areas. We conclude that L. intracellularis is widely prevalent in commercial pigs in China

Secreted Phosphoprotein 24 kD (Spp24) and Spp14 Affect TGF-β Induced Bone Formation Differently

Transforming growth factor-β (TGF-β) and bone morphogenetic proteins (BMPs) have opposing but complementary functions in directing bone growth, repair, and turnover. Both are found in the bone matrix. Proteins that bind to and affect the activity of these growth factors will determine the relative abundance of the growth factors and, therefore, regulate bone formation. Secreted phosphoprotein 24 kD (Spp24) is a bone matrix protein that has been demonstrated to bind to and affect the activity of BMPs. The arginine-rich carboxy terminus of Spp24 is proteolytically processed to produce three other predictable truncation products (Spp18.1, Spp16.0, and Spp14.5). In this work, we report that kinetic data obtained by surface plasmon resonance demonstrate that Spp24 and the three C-terminal truncation products all bind to TGF-β1 and TGF-β2 with a similar but somewhat less affinity than they bind BMP-2; that, as in the case of BMP-2, the full-length (FL) form of Spp24 binds TGF-β with greater affinity than do the truncation products; that FL-Spp24 inhibits TGF-β2 induced bone formation in vivo, but Spp14.5 does not; and that co-administration of FL-Spp24 or Spp14.5 with TGF-β2 in vivo is associated with a reduction in the amount of cartilage, relative to new bone, present at the site of injection. This finding is consistent with the observation that low-dose TGF-β administration in vivo is associated with greater bone formation than high-dose TGF-β administration, and suggests that one function of Spp24 and its truncation products is to down-regulate local TGF-β activity or availability during bone growth and development. The similarities and differences of the interactions between Spp24 proteins and TGF-β compared to the interaction of the Spp24 proteins and BMPs have significant implications with respect to the regulation of bone metabolism and with respect to engineering therapeutic proteins for skeletal disorders. © 2013 Tian et al

Peroxo Species Formed in the Bulk of Silicate Cathodes

Oxygen redox in Li‐rich oxides may boost the energy density of lithium‐ion batteries by incorporating oxygen chemistry in solid cathodes. However, oxygen redox in the bulk usually entangles with voltage hysteresis and oxygen release, resulting in a prolonged controversy in literature on oxygen transformation. Here, we report spectroscopic evidence of peroxo species formed and confined in silicate cathodes amid oxygen redox at high voltage, accompanied by Co$^{2+}$/Co$^{3+}$ redox dominant at low voltage. First‐principles calculations reveal that localized electrons on dangling oxygen drive the O‐O dimerization. The covalence between the binding cation and the O‐O dimer determines the degree of electron transfer in oxygen transformation. Dimerization induces irreversible structural distortion and slow kinetics. But peroxo formation can minimize the voltage drop and volume expansion in cumulative cationic and anionic redox. These findings offer insights into oxygen redox in the bulk for the rational design of high‐energy‐density cathodes

Highly Selective Production of Ethylene by the Electroreduction of Carbon Monoxide.

Conversion of carbon monoxide to high value-added ethylene with high selectivity by traditional syngas conversion process is challenging because of the limitation of Anderson-Schulz-Flory distribution. Herein we report a direct electrocatalytic process for highly selective ethylene production from CO reduction with water over Cu catalysts at room temperature and ambient pressure. An unprecedented 52.7 % Faradaic efficiency of ethylene formation is achieved through optimization of cathode structure to facilitate CO diffusion at the surface of the electrode and Cu catalysts to enhance the C-C bond coupling. The highly selective ethylene production is almost without other carbon-based byproducts (e.g. C1 -C4 hydrocarbons and CO2 ) and avoids the drawbacks of the traditional Fischer-Tropsch process that always delivers undesired products. This study provides a new and promising strategy for highly selective production of ethylene from the abundant industrial CO

Enhanced Electron Correlation and Significantly Suppressed Thermal Conductivity in Dirac Nodal-Line Metal Nanowires by Chemical Doping

Enhancing electron correlation in a weakly interacting topological system has great potential to promote correlated topological states of matter with extraordinary quantum properties. Here, the enhancement of electron correlation in a prototypical topological metal, namely iridium dioxide (IrO2), via doping with 3d transition metal vanadium is demonstrated. Single-crystalline vanadium-doped IrO2 nanowires are synthesized through chemical vapor deposition where the nanowire yield and morphology are improved by creating rough surfaces on substrates. Vanadium doping leads to a dramatic decrease in Raman intensity without notable peak broadening, signifying the enhancement of electron correlation. The enhanced electron correlation is further evidenced by transport studies where the electrical resistivity is greatly increased and follows an unusual √ T dependence on the temperature (T). The lattice thermal conductivity is suppressed by an order of magnitude via doping even at room temperature where phonon-impurity scattering becomes less important. Density functional theory calculations suggest that the remarkable reduction of thermal conductivity arises from the complex phonon dispersion and reduced energy gap between phonon branches, which greatly enhances phase space for phonon–phonon Umklapp scattering. This work demonstrates a unique system combining 3d and 5d transition metals in isostructural materials to enrich the system with various types of interactions