Showing papers by "Waseda University published in 2017"
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20 Jul 2017TL;DR: This work presents a novel approach for image completion that results in images that are both locally and globally consistent, with a fully-convolutional neural network that can complete images of arbitrary resolutions by filling-in missing regions of any shape.
Abstract: We present a novel approach for image completion that results in images that are both locally and globally consistent. With a fully-convolutional neural network, we can complete images of arbitrary resolutions by filling-in missing regions of any shape. To train this image completion network to be consistent, we use global and local context discriminators that are trained to distinguish real images from completed ones. The global discriminator looks at the entire image to assess if it is coherent as a whole, while the local discriminator looks only at a small area centered at the completed region to ensure the local consistency of the generated patches. The image completion network is then trained to fool the both context discriminator networks, which requires it to generate images that are indistinguishable from real ones with regard to overall consistency as well as in details. We show that our approach can be used to complete a wide variety of scenes. Furthermore, in contrast with the patch-based approaches such as PatchMatch, our approach can generate fragments that do not appear elsewhere in the image, which allows us to naturally complete the images of objects with familiar and highly specific structures, such as faces.
1,961 citations
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TL;DR: An overview of recent developments achieved in the fabrication of porous MOF-derived nanostructures including carbons, metal oxides, metal chalcogenides (metal sulfides and selenides), metal carbide, metal phosphides and their composites are provided.
Abstract: The emergence of metal-organic frameworks (MOFs) as a new class of crystalline porous materials is attracting considerable attention in many fields such as catalysis, energy storage and conversion, sensors, and environmental remediation due to their controllable composition, structure and pore size. MOFs are versatile precursors for the preparation of various forms of nanomaterials as well as new multifunctional nanocomposites/hybrids, which exhibit superior functional properties compared to the individual components assembling the composites. This review provides an overview of recent developments achieved in the fabrication of porous MOF-derived nanostructures including carbons, metal oxides, metal chalcogenides (metal sulfides and selenides), metal carbides, metal phosphides and their composites. Finally, the challenges and future trends and prospects associated with the development of MOF-derived nanomaterials are also examined.
710 citations
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ETH Zurich1, Centre national de la recherche scientifique2, University of Évry Val d'Essonne3, Institut national de la recherche agronomique4, University of Guelph5, University College Cork6, University of Helsinki7, Wageningen University and Research Centre8, University of British Columbia9, University of Aberdeen10, University of Tokyo11, Waseda University12, Baylor College of Medicine13, Medical University of Graz14, University of Florida15, Okayama University16, Maastricht University17, Statens Serum Institut18, University of Western Ontario19, Shanghai Jiao Tong University20, King's College London21
TL;DR: A standardized DNA extraction method for human fecal samples is recommended, for which transferability across labs was established and which was further benchmarked using a mock community of known composition to improve comparability of human gut microbiome studies and facilitate meta-analyses.
Abstract: Technical variation in metagenomic analysis must be minimized to confidently assess the contributions of microbiota to human health. Here we tested 21 representative DNA extraction protocols on the same fecal samples and quantified differences in observed microbial community composition. We compared them with differences due to library preparation and sample storage, which we contrasted with observed biological variation within the same specimen or within an individual over time. We found that DNA extraction had the largest effect on the outcome of metagenomic analysis. To rank DNA extraction protocols, we considered resulting DNA quantity and quality, and we ascertained biases in estimates of community diversity and the ratio between Gram-positive and Gram-negative bacteria. We recommend a standardized DNA extraction method for human fecal samples, for which transferability across labs was established and which was further benchmarked using a mock community of known composition. Its adoption will improve comparability of human gut microbiome studies and facilitate meta-analyses.
516 citations
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TL;DR: Using gnotobiotic techniques, strains of Klebsiella spp.
Abstract: Intestinal colonization by bacteria of oral origin has been correlated with several negative health outcomes, including inflammatory bowel disease. However, a causal role of oral bacteria ectopically colonizing the intestine remains unclear. Using gnotobiotic techniques, we show that strains of Klebsiella spp. isolated from the salivary microbiota are strong inducers of T helper 1 (TH1) cells when they colonize in the gut. These Klebsiella strains are resistant to multiple antibiotics, tend to colonize when the intestinal microbiota is dysbiotic, and elicit a severe gut inflammation in the context of a genetically susceptible host. Our findings suggest that the oral cavity may serve as a reservoir for potential intestinal pathobionts that can exacerbate intestinal disease.
504 citations
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TL;DR: This paper presents a short overview of the changes to the trigger and data acquisition systems during the first long shutdown of the LHC and shows the performance of the trigger system and its components based on the 2015 proton–proton collision data.
Abstract: During 2015 the ATLAS experiment recorded 3.8 fb(-1) of proton-proton collision data at a centre-of-mass energy of 13 TeV. The ATLAS trigger system is a crucial component of the experiment, respons ...
488 citations
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TL;DR: In this paper, a facile metal-organic framework-engaged strategy was presented to synthesize hollow Co3S4@MoS2 heterostructures as efficient bifunctional catalysts for both H2 and O2 generation.
Abstract: Herein, we present a facile metal–organic framework-engaged strategy to synthesize hollow Co3S4@MoS2 heterostructures as efficient bifunctional catalysts for both H2 and O2 generation. The well-known cobalt-based metal–organic zeolitic imidazolate frameworks (ZIF-67) are used not only as the morphological template but also as the cobalt precursor. During the two-step temperature-raising hydrothermal process, ZIF-67 polyhedrons are first transformed to hollow cobalt sulfide polyhedrons by sulfidation, and then molybdenum disulfide nanosheets further grow and deposit on the surface of hollow cobalt sulfide polyhedrons at the increased temperature. The crystalline hollow Co3S4@MoS2 heterostructures are finally obtained after subsequent thermal annealing under a N2 atmosphere. Due to the synergistic effects between the hydrogen evolution reaction active catalyst of MoS2 and the oxygen evolution reaction active catalyst of Co3S4, the obtained hollow Co3S4@MoS2 heterostructures exhibit outstanding bifunctional ...
467 citations
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TL;DR: Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS and is exploited to apply a local energy calibration and corrections depending on the nature of the cluster.
Abstract: The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.
438 citations
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TL;DR: In this review, recent advances in metal-catalyzed cross-coupling reactions of aromatic esters and amides are discussed.
Abstract: Catalytic cross-coupling reactions of aromatic esters and amides have recently gained considerable attention from synthetic chemists as de novo and efficient synthetic methods to form C–C and C–heteroatom bonds. Esters and amides can be used as diversifiable groups in metal-catalyzed cross-coupling: in a decarbonylative manner, they can be utilized as leaving groups, whereas in a non-decarbonylative manner, they can form ketone derivatives. In this review, recent advances of this research topic are discussed.
335 citations
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TL;DR: In this article, a search for new resonant and non-resonant high-mass phenomena in dielectron and dimuon fi nal states was conducted using 36 : 1 fb(-1) of proton-proton collision data.
Abstract: A search is conducted for new resonant and non-resonant high-mass phenomena in dielectron and dimuon fi nal states. The search uses 36 : 1 fb(-1) of proton-proton collision data, collected at root ...
329 citations
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TL;DR: Foul-release (FR) nanocoatings have been extensively investigated because of their non-stick, ecological, and economic advantages as mentioned in this paper, which deter any fouling attachment through physical anti-adhesion terminology.
314 citations
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TL;DR: In this paper, the authors improved on the strategy used in the literature to identify the spillover effect of horizontal foreign direct investment (FDI) by taking advantage of the plausibly exogenous relaxation of FDI regulations on China's World Trade Organization accession at the end of 2001.
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TL;DR: All-carbon layer-by-layer motif architectures are synthesized by introducing 2D ordered mesoporous carbons (OMC) within the interlayer space of 2D nanomaterials by constructing ion-accessible OMC within the 2D host material.
Abstract: Although various two-dimensional (2D) nanomaterials have been explored as promising capacitive materials due to their unique layered structure, their natural restacking tendency impedes electrolyte transport and significantly restricts their practical applications. Herein, we synthesize all-carbon layer-by-layer motif architectures by introducing 2D ordered mesoporous carbons (OMC) within the interlayer space of 2D nanomaterials. As a proof of concept, MXenes are selected as 2D hosts to design 2D-2D heterostructures. Further removing the metal elements from MXenes leads to the formation of all-carbon 2D-2D heterostructures consisting of alternating layers of MXene-derived carbon (MDC) and OMC. The OMC layers intercalated with the MDC layers not only prevent restacking but also facilitate ion diffusion and electron transfer. The performance of the obtained hybrid carbons as supercapacitor electrodes demonstrates their potential for upcoming electronic devices. This method allows to overcome the restacking and blocking of 2D nanomaterials by constructing ion-accessible OMC within the 2D host material.
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TL;DR: Experimental results show that the proposing MIMAGA-Selection method significantly reduces the dimension of gene expression data and removes the redundancies for classification and the reduced gene expression dataset provides highest classification accuracy compared to conventional feature selection algorithms.
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TL;DR: In this paper, Dijet events are studied in the proton-proton collision dataset recorded at root s = 13 TeV with the ATLAS detector at the Large Hadron Collider in 2015 and 2016.
Abstract: Dijet events are studied in the proton-proton collision dataset recorded at root s = 13 TeV with the ATLAS detector at the Large Hadron Collider in 2015 and 2016, corresponding to integrated lumino ...
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TL;DR: In this paper, the authors investigated the interactions between K ions and organic electrolyte solvents for application in nonaqueous K-ion batteries, which have recently drawn interest as novel rechargeable batteries.
Abstract: Ion–solvent interactions play a crucial role in secondary battery systems: the desolvation of ions at an electrode/electrolyte interface can be the rate-determining step of a battery reaction, for instance. The present theoretical study investigates the interactions between K ions and organic electrolyte solvents for application in non-aqueous K-ion batteries, which have recently drawn interest as novel rechargeable batteries. Compared to Li, Na, and Mg ions, K ions display the lowest interaction energy, reflecting the large ionic radius and weak Lewis acidity of K. The weak interaction of K ions with solvents is consistent with the high rate capability exhibited by K-ion batteries and the relatively low solubility of K-ion salts observed experimentally.
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TL;DR: In this paper, the authors demonstrate the redox-active properties of self-polymerized dopamine on the surface of few-walled carbon nanotubes (FWNTs), which can be used as organic cathode materials for both Li- and Na-ion batteries.
Abstract: Self-polymerized dopamine is a versatile coating material that has various oxygen and nitrogen functional groups. Here, we demonstrate the redox-active properties of self-polymerized dopamine on the surface of few-walled carbon nanotubes (FWNTs), which can be used as organic cathode materials for both Li- and Na-ion batteries. We reveal the multiple redox reactions between self-polymerized dopamine and electrolyte ions in the high voltage region from 2.5 to 4.1 V vs. Li using both density functional theory (DFT) calculations and electrochemical measurements. Free-standing and flexible hybrid electrodes are assembled using a vacuum filtration method, which have a 3D porous network structure consisting of polydopamine coated FWNTs. The hybrid electrodes exhibit gravimetric capacities of ∼133 mA h g−1 in Li-cells and ∼109 mA h g−1 in Na-cells utilizing double layer capacitance from FWNTs and multiple redox-reactions from polydopamine. The polydopamine itself within the hybrid film can store high gravimetric capacities of ∼235 mA h g−1 in Li-cells and ∼213 mA h g−1 in Na-cells. In addition, the hybrid electrodes show a high rate-performance and excellent cycling stability, suggesting that self-polymerized dopamine is a promising cathode material for organic rechargeable batteries.
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TL;DR: Findings reveal that H1 imparts a strong degree of asymmetry to the nucleosome, which is likely to influence the assembly and architecture of higher-order structures.
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TL;DR: In this paper, the authors investigated the universal approximation property of neural networks with unbounded activation functions, such as the rectified linear unit (ReLU), and showed that the ReLU network can be analyzed by the ridgelet transform with respect to Lizorkin distributions.
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TL;DR: Surprisingly, the high surface area mesoporous structure of the Rh catalyst was thermally stable up to 400 °C and enables superior catalytic activity for the remediation of nitric oxide (NO) in lean-burn exhaust containing high concentrations of O2.
Abstract: Mesoporous noble metals are an emerging class of cutting-edge nanostructured catalysts due to their abundant exposed active sites and highly accessible surfaces Although various noble metal (eg Pt, Pd and Au) structures have been synthesized by hard- and soft-templating methods, mesoporous rhodium (Rh) nanoparticles have never been generated via chemical reduction, in part due to the relatively high surface energy of rhodium (Rh) metal Here we describe a simple, scalable route to generate mesoporous Rh by chemical reduction on polymeric micelle templates [poly(ethylene oxide)-b-poly(methyl methacrylate) (PEO-b-PMMA)] The mesoporous Rh nanoparticles exhibited a ∼26 times enhancement for the electrocatalytic oxidation of methanol compared to commercially available Rh catalyst Surprisingly, the high surface area mesoporous structure of the Rh catalyst was thermally stable up to 400 °C The combination of high surface area and thermal stability also enables superior catalytic activity for the remediation of nitric oxide (NO) in lean-burn exhaust containing high concentrations of O2 Mesoporous noble metal nanostructures offer great promise in catalytic applications Here, Yamauchi and co-workers synthesize mesoporous rhodium nanoparticles using polymeric micelle templates, and report appreciable activities for methanol oxidation and NO remediation
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Hosei University1, University of Tokyo2, Kyoto University3, Osaka City University4, University of Electro-Communications5, Goddard Space Flight Center6, National Institutes of Natural Sciences, Japan7, Waseda University8, Hirosaki University9, California Institute of Technology10, Nihon University11, Ochanomizu University12, Tokyo Keizai University13, Raman Research Institute14, Tohoku University15, Rikkyo University16, University of Texas at Austin17, Osaka University18, Shibaura Institute of Technology19, National Institute of Advanced Industrial Science and Technology20, Tokai University21, National Institute of Information and Communications Technology22, Kindai University23, University of Wisconsin–Milwaukee24, Albert Einstein Institution25, Liverpool John Moores University26, Hiroshima University27, Rochester Institute of Technology28, National Defense Academy of Japan29, Niigata University30, University of Southampton31, Osaka Institute of Technology32, University of Tübingen33, Nagoya University34, Nagaoka University of Technology35, Tokyo University of Science36, Tokyo Institute of Technology37, Japan Aerospace Exploration Agency38
TL;DR: DECIGO (DECi-hertz Interferometer Gravitational wave Observatory) is the planned Japanese space gravitational wave antenna, aiming to detect gravitational waves from astrophysically and cosmologically significant sources mainly between 1 Hz and 10 Hz as mentioned in this paper.
Abstract: DECIGO (DECi-hertz Interferometer Gravitational wave Observatory) is the planned Japanese space gravitational wave antenna, aiming to detect gravitational waves from astrophysically and cosmologically significant sources mainly between 01 Hz and 10 Hz and thus to open a new window for gravitational wave astronomy and for the universe DECIGO will consists of three drag-free spacecraft arranged in an equilateral triangle with 1000 km arm lengths whose relative displacements are measured by a differential Fabry-Perot interferometer, and four units of triangular Fabry-Perot interferometers are arranged on heliocentric orbit around the sun DECIGO is vary ambitious mission, we plan to launch DECIGO in era of 2030s after precursor satellite mission, B-DECIGO B-DECIGO is essentially smaller version of DECIGO: B-DECIGO consists of three spacecraft arranged in an triangle with 100 km arm lengths orbiting 2000 km above the surface of the earth It is hoped that the launch date will be late 2020s for the present
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01 Apr 2017TL;DR: A practical state-of-the-art method to develop a machine-learning-based humanoid robot that can work as a production line worker and exhibits the following characteristics: task performing capability, task reiteration ability, generalizability, and easy applicability.
Abstract: We propose a practical state-of-the-art method to develop a machine-learning-based humanoid robot that can work as a production line worker. The proposed approach provides an intuitive way to collect data and exhibits the following characteristics: task performing capability, task reiteration ability, generalizability, and easy applicability. The proposed approach utilizes a real-time user interface with a monitor and provides a first-person perspective using a head-mounted display. Through this interface, teleoperation is used for collecting task operating data, especially for tasks that are difficult to be applied with a conventional method. A two-phase deep learning model is also utilized in the proposed approach. A deep convolutional autoencoder extracts images features and reconstructs images, and a fully connected deep time delay neural network learns the dynamics of a robot task process from the extracted image features and motion angle signals. The “Nextage Open” humanoid robot is used as an experimental platform to evaluate the proposed model. The object folding task utilizing with 35 trained and 5 untrained sensory motor sequences for test. Testing the trained model with online generation demonstrates a 77.8% success rate for the object folding task.
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TL;DR: In this paper, a 3D ordered mesoporous Fe-N/C with open porous structure is successfully synthesized and the obtained shape is a rhombic dodecahedron which corresponds to a single mesoporus crystal with body-centered cubic structure (Im-3m).
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TL;DR: FMT for patients with IBS is safe, and relatively effective, and Bifidobacterium-rich fecal donor may be a positive predictor for successful FMT, which showed that FMT improved stool form and psychological status of IBS patients.
Abstract: Background/Aims: Dysbiosis is associated with various systemic disorders including irritable bowel syndrome (IBS). Fecal microbiota transplantation (FMT) might re
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TL;DR: It is suggested that patients with HF harbor significantly altered gut microbiota, which varies further according to age, and new concept of heart-gut axis has a great potential for breakthroughs in the development of novel diagnostic and therapeutic approach for HF.
Abstract: Emerging evidence has suggested a potential impact of gut microbiota on the pathophysiology of heart failure (HF). However, it is still unknown whether HF is associated with dysbiosis in gut microbiota. We investigated the composition of gut microbiota in patients with HF to elucidate whether gut microbial dysbiosis is associated with HF. We performed 16S ribosomal RNA gene sequencing of fecal samples obtained from 12 HF patients and 12 age-matched healthy control (HC) subjects, and analyzed the differences in gut microbiota. We further compared the composition of gut microbiota of 12 HF patients younger than 60 years of age with that of 10 HF patients 60 years of age or older. The composition of gut microbial communities of HF patients was distinct from that of HC subjects in both unweighted and weighted UniFrac analyses. Eubacterium rectale and Dorea longicatena were less abundant in the gut microbiota of HF patients than in that of HC subjects. Compared to younger HF patients, older HF patients had diminished proportions of Bacteroidetes and larger quantities of Proteobacteria. The genus Faecalibacterium was depleted, while Lactobacillus was enriched in the gut microbiota of older HF patients. These results suggest that patients with HF harbor significantly altered gut microbiota, which varies further according to age. New concept of heart-gut axis has a great potential for breakthroughs in the development of novel diagnostic and therapeutic approach for HF.
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TL;DR: This paper surveys different measurement techniques and strategies for range based and range free localization with an emphasis on the latter and discusses different localization-based applications, where the estimation of the location information is crucial.
Abstract: Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors that communicate with each other in ad-hoc fashion. The task of determining physical coordinates of sensor nodes in WSNs is known as localization or positioning and is a key factor in today’s communication systems to estimate the place of origin of events. As the requirement of the positioning accuracy for different applications varies, different localization methods are used in different applications and there are several challenges in some special scenarios such as forest fire detection. In this paper, we survey different measurement techniques and strategies for range based and range free localization with an emphasis on the latter. Further, we discuss different localization-based applications, where the estimation of the location information is crucial. Finally, a comprehensive discussion of the challenges such as accuracy, cost, complexity, and scalability are given.
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TL;DR: In this paper, a new generation of smart de- and remanufacturing systems showing higher levels of automation, flexibility and adaptability to changing material mixtures and values is emerging and there is a need for systematizing the existing approaches to support their operations.
Abstract: In the recent years, increasing attention has been posed towards enhancing the sustainability of manufacturing processes by reducing the consumption of resources and key materials, the energy consumption and the environmental footprint, while also increasing companies’ competitiveness in global market contexts. De- and remanufacturing includes the set of technologies/systems, tools and knowledge-based methods to recover and reuse functions and materials from industrial waste and post-consumer products, under a Circular Economy perspective. This new paradigm can potentially support the sustainability challenges in strategic manufacturing sectors, such as aeronautics, automotive, electronics, consumer goods, and mechatronics. A new generation of smart de- and remanufacturing systems showing higher levels of automation, flexibility and adaptability to changing material mixtures and values is emerging and there is a need for systematizing the existing approaches to support their operations. Such innovative de- and remanufacturing system design, management and control approaches as well as advanced technological enablers have a key role to support the Circular Economy paradigm. This paper revises system level problems, methods and tools to support this paradigm and highlights the main challenges and opportunities towards a new generation of advanced de- and remanufacturing systems.
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TL;DR: In this paper, a simple method is developed to assemble Mo2C nanocrystals on the surfaces of hollow, highly conductive mesoporous nanoparticles, which in turn enhance the catalytic performance for the oxygen reduction reaction (ORR).
Abstract: A simple method is developed to assemble Mo2C nanocrystals on the surfaces of hollow, highly conductive mesoporous nanoparticles. Diblock copolymer (PS-b-PEO) micelles are used as templates to assist in the fast complexation of molybdate (MoO42−) and polydopamine (PDA) precursors to make hollow precursor MoO42−/PDA/PS-b-PEO particles. Then these particles are carbonized to generate mesoporous N-doped carbon nanosheets riddled with ultrafine molybdenum carbide (Mo2C) nanoparticles (MMo2C/NCS). An N-doped carbon matrix serves as an electron conductor and helps to prevent the aggregation of the Mo2C nanoparticles. The Mo2C nanoparticles in turn enhance the catalytic performance for the oxygen reduction reaction (ORR). The unique mesoporous 2D nanosheet and its derived 3D hollow structure expose numerous active catalytic sites while enabling free diffusion of the electrolyte and mass transfer. Based on these properties, MMo2C/NCS show enhanced catalytic activity for the ORR.
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TL;DR: In this article, a solution-processed polymer layer between the perovskite layer and the hole-transporting layer was added to improve the performance of perov-skite solar cells.
Abstract: Solution-processed organo-lead halide perovskite solar cells with deep pinholes in the perovskite layer lead to shunt-current leakage in devices. Herein, we report a facile method for improving the performance of perovskite solar cells by inserting a solution-processed polymer layer between the perovskite layer and the hole-transporting layer. The photovoltaic conversion efficiency of the perovskite solar cell increased to 18.1% and the stability decreased by only about 5% during 20 days of exposure in moisture ambient conditions through the incorporation of a poly(methyl methacrylate) (PMMA) polymer layer. The improved photovoltaic performance of devices with a PMMA layer is attributed to the reduction of carrier recombination loss from pinholes, boundaries, and surface states of perovskite layer. The significant gain generated by this simple procedure supports the use of this strategy in further applications of thin-film optoelectronic devices.
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University of Lethbridge1, University of British Columbia2, University of Southern Queensland3, University of Queensland4, Arizona State University5, Glasgow Caledonian University6, Tokyo Medical University7, University College London8, Waseda University9, Baker IDI Heart and Diabetes Institute10, University of Lisbon11, Australian Catholic University12, University of Ontario Institute of Technology13
TL;DR: There appears to be an association between ST and geriatric-relevant health outcomes, although there is insufficient longitudinal evidence to determine a dose–response relationship or a threshold for clinically relevant risk.
Abstract: Sedentary time (ST) is an important risk factor for a variety of health outcomes in older adults. Consensus is needed on future research directions so that collaborative and timely efforts can be made globally to address this modifiable risk factor. In this review, we examined current literature to identify gaps and inform future research priorities on ST and healthy ageing. We reviewed three primary topics:(1) the validity/reliability of self-report measurement tools, (2) the consequences of prolonged ST on geriatric-relevant health outcomes (physical function, cognitive function, mental health, incontinence and quality of life) and(3) the effectiveness of interventions to reduce ST in older adults. Methods A trained librarian created a search strategy that was peer reviewed for completeness. Results Self-report assessment of the context and type of ST is important but the tools tend to underestimate total ST. There appears to be an association between ST and geriatric-relevant health outcomes, although there is insufficient longitudinal evidence to determine a dose-response relationship or a threshold for clinically relevant risk. The type of ST may also affect health; some cognitively engaging sedentary behaviours appear to benefit health, while time spent in more passive activities may be detrimental. Short-term feasibility studies of individual-level ST interventions have been conducted; however, few studies have appropriately assessed the impact of these interventions on geriatric-relevant health outcomes, nor have they addressed organisation or environment level changes. Research is specifically needed to inform evidence-based interventions that help maintain functional autonomy among older adults. This consensus statement has been endorsed by the following societies: Academy of Geriatric Physical Therapy, Exercise & Sports Science Australia, Canadian Centre for Activity and Aging, Society of Behavioral Medicine, and the National Centre for Sport and Exercise Medicine.
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TL;DR: This article provides a comprehensive review of the state-of-the-art contributions from the perspective of software defined networking and machineto- machine integration, and the overall design of the proposed software-defined machine-to-machine (SD-M2M) framework is presented.
Abstract: The successful realization of smart energy management relies on ubiquitous and reliable information exchange among millions of sensors and actuators deployed in the field with little or no human intervention. This motivates us to propose a unified communication framework for smart energy management by exploring the integration of software-defined networking with machine-to-machine communication. In this article, first we provide a comprehensive review of the state-of-the-art contributions from the perspective of software defined networking and machineto- machine integration. Second, the overall design of the proposed software-defined machine-to-machine (SD-M2M) framework is presented, with an emphasis on its technical contributions to cost reduction, fine granularity resource allocation, and end-to-end quality of service guarantee. Then a case study is conducted for an electric vehicle energy management system to validate the proposed SD-M2M framework. Finally, we identify several open issues and present key research opportunities.