Waseda University

About: Waseda University is a education organization based out in Tokyo, Japan. It is known for research contribution in the topics: Large Hadron Collider & Catalysis. The organization has 24220 authors who have published 46859 publications receiving 837855 citations. The organization is also known as: Waseda daigaku & Sōdai.

A New Tetradentate β-Diketonate−Europium Chelate That Can Be Covalently Bound to Proteins for Time-Resolved Fluoroimmunoassay

Abstract: A new chlorosulfonylated tetradentate β-diketone, 4,4‘-bis(1‘‘,1‘‘,1‘‘,2‘‘,2‘‘,3‘‘,3‘‘-heptafluoro-4‘‘,6‘‘-hexanedion-6‘‘-yl)chlorosulfo-o-terphenyl (BHHCT), was synthesized as a chelating label for Eu3+. BHHCT can be covalently bound to proteins under mild conditions and forms a strongly fluorescent chelate with Eu3+. Bovine serum albumin (BSA) and streptavidin (SA) were labeled with BHHCH−Eu3+, and the latter was used for time-resolved fluoroimmunoassay of α-fetoprotein (AFP) in human sera. A remarkably high sensitivity was obtained, with a detection limit of 4.1 × 10-3 pg/mL, which corresponds to an improvement of about 4−5 orders of magnitude, compared to those of all conventional immunoassays including fluoroimmunoassay, enzyme immunoassay, and radioimmunoassay. The high sensitivity has been attained both by strong fluorescence of the present label and by the extremely suppressed background level brought about by the direct labeling of proteins with the β-diketone−Eu3+ complex. A general consideratio...

Tunable carbon nanotube thin-film transistors produced exclusively via inkjet printing

Abstract: Inkjet printing in electronics production has attracted considerable attention for a wide-range of applications because it is an environmentally friendly and low-cost technique. [ 1–5 ] In addition to excellent charge-transport properties, materials for inkjet printing must meet other key requirements, such as high chemical stability, low-temperature processability, low hysteresis, and low-voltage operation. In the past, materials satisfying these criteria have not been available. Here, we demonstrate low-cost green manufacturing via precisely controlled inkjet printing of singlewalled carbon nanotube (SWCNT) fi lms. This transistor exceeds the performance of conventional organic transistors (a mobility of 1.6 to 4.2 cm 2 V − 1 s − 1 and an on/off ratio of 4 to 5 digits) and is fabricated at moderate temperatures (80 ° C). We also demonstrate the production of exclusively inkjetprinted SWCNT transistors with printable ionic-liquid gate dielectrics. Printable technology has the potential to drastically reduce ecological impact, energy consumption during manufacturing, and wasted materials by controlling the quantity and location of ink deposition. Inkjet technology is exceptionally promising because patterns can be generated without any material waste, leading to drastic reductions in production costs and in environmental impact. Materials for printable electronics must satisfy several requirements, such as high transport properties, chemical stability, and low-temperature processability. Research in this area has been focused largely on organic semiconductors [ 1–5 ] because carrier mobilities comparable to those of amorphous silicon ( ≤ 1 cm 2 V − 1 s − 1 ) are needed to create printable electronics. Although highly crystalline organic

A Secure IoT Service Architecture With an Efficient Balance Dynamics Based on Cloud and Edge Computing

Abstract: The Internet of Things (IoT)-Cloud combines the IoT and cloud computing, which not only enhances the IoT’s capability but also expands the scope of its applications. However, it exhibits significant security and efficiency problems that must be solved. Internal attacks account for a large fraction of the associated security problems, however, traditional security strategies are not capable of addressing these attacks effectively. Moreover, as repeated/similar service requirements become greater in number, the efficiency of IoT-Cloud services is seriously affected. In this paper, a novel architecture that integrates a trust evaluation mechanism and service template with a balance dynamics based on cloud and edge computing is proposed to overcome these problems. In this architecture, the edge network and the edge platform are designed in such a way as to reduce resource consumption and ensure the extensibility of trust evaluation mechanism, respectively. To improve the efficiency of IoT-Cloud services, the service parameter template is established in the cloud and the service parsing template is established in the edge platform. Moreover, the edge network can assist the edge platform in establishing service parsing templates based on the trust evaluation mechanism and meet special service requirements. The experimental results illustrate that this edge-based architecture can improve both the security and efficiency of IoT-Cloud systems.

Performance of missing transverse momentum reconstruction with the ATLAS detector using proton-proton collisions at s√ = 13 TeV

Abstract: The performance of the missing transverse momentum ( ETmiss ) reconstruction with the ATLAS detector is evaluated using data collected in proton-proton collisions at the LHC at a centre-of-mass energy of 13 TeV in 2015. To reconstruct ETmiss , fully calibrated electrons, muons, photons, hadronically decaying τ-leptons , and jets reconstructed from calorimeter energy deposits and charged-particle tracks are used. These are combined with the soft hadronic activity measured by reconstructed charged-particle tracks not associated with the hard objects. Possible double counting of contributions from reconstructed charged-particle tracks from the inner detector, energy deposits in the calorimeter, and reconstructed muons from the muon spectrometer is avoided by applying a signal ambiguity resolution procedure which rejects already used signals when combining the various ETmiss contributions. The individual terms as well as the overall reconstructed ETmiss are evaluated with various performance metrics for scale (linearity), resolution, and sensitivity to the data-taking conditions. The method developed to determine the systematic uncertainties of the ETmiss scale and resolution is discussed. Results are shown based on the full 2015 data sample corresponding to an integrated luminosity of 3.2fb-1 .

Forecasting the Wind Generation Using a Two-Stage Network Based on Meteorological Information

Abstract: This paper proposes a practical and effective model for the generation forecasting of a wind farm with an emphasis on its scheduling and trading in a wholesale electricity market. A novel forecasting model is developed based on indepth investigations of meteorological information. This model adopts a two-stage hybrid network with Bayesian clustering by dynamics and support vector regression. The proposed structure is robust with different input data types and can deal with the nonstationarity of wind speed and generation series well. Once the network is trained, we can straightforward predict the 48-h ahead wind power generation. To demonstrate the effectiveness, the model is applied and tested on a 74-MW wind farm located in the southwest Oklahoma of the United States.