Tokyo Institute of Technology

A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented in this paper. The premise of an implication is the description of fuzzy subspace of inputs and its consequence is a linear input-output relation. The method of identification of a system using its input-output data is then shown. Two applications of the method to industrial processes are also discussed: a water cleaning process and a converter in a steel-making process.

We report that a layered iron-based compound LaOFeAs undergoes superconducting transition under doping with F- ions at the O2- site. The transition temperature (Tc) exhibits a trapezoid shape dependence on the F- content, with the highest Tc of ∼26 K at ∼11 atom %.

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
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\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
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\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

Heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) respond to a variety of different external stimuli and activate G proteins. GPCRs share many structural features, including a bundle of seven transmembrane alpha helices connected by six loops of varying lengths. We determined the structure of rhodopsin from diffraction data extending to 2.8 angstroms resolution. The highly organized structure in the extracellular region, including a conserved disulfide bridge, forms a basis for the arrangement of the seven-helix transmembrane motif. The ground-state chromophore, 11-cis-retinal, holds the transmembrane region of the protein in the inactive conformation. Interactions of the chromophore with a cluster of key residues determine the wavelength of the maximum absorption. Changes in these interactions among rhodopsins facilitate color discrimination. Identification of a set of residues that mediate interactions between the transmembrane helices and the cytoplasmic surface, where G-protein activation occurs, also suggests a possible structural change upon photoactivation.

We present an analysis of atmospheric neutrino data from a 33.0 kton yr (535-day) exposure of the Super-Kamiokande detector. The data exhibit a zenith angle dependent deficit of muon neutrinos which is inconsistent with expectations based on calculations of the atmospheric neutrino flux. Experimental biases and uncertainties in the prediction of neutrino fluxes and cross sections are unable to explain our observation. The data are consistent, however, with two-flavor ${\ensuremath{\nu}}_{\ensuremath{\mu}}\ensuremath{\leftrightarrow}{\ensuremath{\nu}}_{\ensuremath{\tau}}$ oscillations with ${sin}^{2}2\ensuremath{\theta}>0.82$ and $5\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}<\ensuremath{\Delta}{m}^{2}<6\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}3}\mathrm{eV}{}^{2}$ at 90% confidence level.

(Abridged) The Large Area Telescope (Fermi/LAT, hereafter LAT), the primary instrument on the Fermi Gamma-ray Space Telescope (Fermi) mission, is an imaging, wide field-of-view, high-energy gamma-ray telescope, covering the energy range from below 20 MeV to more than 300 GeV. This paper describes the LAT, its pre-flight expected performance, and summarizes the key science objectives that will be addressed. On-orbit performance will be presented in detail in a subsequent paper. The LAT is a pair-conversion telescope with a precision tracker and calorimeter, each consisting of a 4x4 array of 16 modules, a segmented anticoincidence detector that covers the tracker array, and a programmable trigger and data acquisition system. Each tracker module has a vertical stack of 18 x,y tracking planes, including two layers (x and y) of single-sided silicon strip detectors and high-Z converter material (tungsten) per tray. Every calorimeter module has 96 CsI(Tl) crystals, arranged in an 8 layer hodoscopic configuration with a total depth of 8.6 radiation lengths. The aspect ratio of the tracker (height/width) is 0.4 allowing a large field-of-view (2.4 sr). Data obtained with the LAT are intended to (i) permit rapid notification of high-energy gamma-ray bursts (GRBs) and transients and facilitate monitoring of variable sources, (ii) yield an extensive catalog of several thousand high-energy sources obtained from an all-sky survey, (iii) measure spectra from 20 MeV to more than 50 GeV for several hundred sources, (iv) localize point sources to 0.3 - 2 arc minutes, (v) map and obtain spectra of extended sources such as SNRs, molecular clouds, and nearby galaxies, (vi) measure the diffuse isotropic gamma-ray background up to TeV energies, and (vii) explore the discovery space for dark matter.

The Transiting Exoplanet Survey Satellite (TESS) will search for planets transiting bright and nearby stars. TESS has been selected by NASA for launch in 2017 as an Astrophysics Explorer mission. The spacecraft will be placed into a highly elliptical 13.7-day orbit around the Earth. During its 2-year mission, TESS will employ four wide-field optical charge-coupled device cameras to monitor at least 200,000 main-sequence dwarf stars with IC≈4−13 for temporary drops in brightness caused by planetary transits. Each star will be observed for an interval ranging from 1 month to 1 year, depending mainly on the star’s ecliptic latitude. The longest observing intervals will be for stars near the ecliptic poles, which are the optimal locations for follow-up observations with the James Webb Space Telescope. Brightness measurements of preselected target stars will be recorded every 2 min, and full frame images will be recorded every 30 min. TESS stars will be 10 to 100 times brighter than those surveyed by the pioneering Kepler mission. This will make TESS planets easier to characterize with follow-up observations. TESS is expected to find more than a thousand planets smaller than Neptune, including dozens that are comparable in size to the Earth. Public data releases will occur every 4 months, inviting immediate community-wide efforts to study the new planets. The TESS legacy will be a catalog of the nearest and brightest stars hosting transiting planets, which will endure as highly favorable targets for detailed investigations.

Photosynthesis uses light energy to drive the oxidation of water at an oxygen-evolving catalytic site within photosystem II (PSII). We report the structure of PSII of the cyanobacterium Thermosynechococcus elongatus at 3.5 angstrom resolution. We have assigned most of the amino acid residues of this 650-kilodalton dimeric multisubunit complex and refined the structure to reveal its molecular architecture. Consequently, we are able to describe details of the binding sites for cofactors and propose a structure of the oxygen-evolving center (OEC). The data strongly suggest that the OEC contains a cubane-like Mn3CaO4 cluster linked to a fourth Mn by a mono-micro-oxo bridge. The details of the surrounding coordination sphere of the metal cluster and the implications for a possible oxygen-evolving mechanism are discussed.

Macroautophagy is mediated by a unique organelle, the autophagosome, which encloses a portion of cytoplasm for delivery to the lysosome. Autophagosome formation is dynamically regulated by starvation and other stresses and involves complicated membrane reorganization. Since the discovery of yeast Atg-related proteins, autophagosome formation has been dissected at the molecular level. In this review we describe the molecular mechanism of autophagosome formation with particular focus on the function of Atg proteins and the long-standing discussion regarding the origin of the autophagosome membrane.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

This work presents a systematic study of the ratio between the integrated intensities of the disorder-induced D and G Raman bands (ID∕IG) in nanographite samples with different crystallite sizes (La) and using different excitation laser energies. The crystallite size La of the nanographite samples was obtained both by x-ray diffraction using synchrotron radiation and directly from scanning tunneling microscopy images. A general equation for the determination of La using any laser energy in the visible range is obtained. Moreover, it is shown that ID∕IG is inversely proportional to the fourth power of the laser energy used in the experiment.

Abstract Summary: Pvclust is an add-on package for a statistical software R to assess the uncertainty in hierarchical cluster analysis. Pvclust can be used easily for general statistical problems, such as DNA microarray analysis, to perform the bootstrap analysis of clustering, which has been popular in phylogenetic analysis. Pvclust calculates probability values (p-values) for each cluster using bootstrap resampling techniques. Two types of p-values are available: approximately unbiased (AU) p-value and bootstrap probability (BP) value. Multiscale bootstrap resampling is used for the calculation of AU p-value, which has superiority in bias over BP value calculated by the ordinary bootstrap resampling. In addition the computation time can be enormously decreased with parallel computing option. Availability: The program is freely distributed under GNU General Public License (GPL) and can directly be installed from CRAN (), the official R package archive. The instruction and program source code are available at Contact: ryota.suzuki@is.titech.ac.jp

Double-decker phthalocyanine complexes with Tb3+ or Dy3+ showed slow magnetization relaxation as a single-molecular property. The temperature ranges in which the behavior was observed were far higher than that of the transition-metal-cluster single-molecule magnets (SMMs). The significant temperature rise results from a mechanism in the relaxation process different from that in the transition-metal-cluster SMMs. The effective energy barrier for reversal of the magnetic moment is determined by the ligand field around a lanthanide ion, which gives the lowest degenerate substate a large |Jz| value and large energy separations from the rest of the substates in the ground-state multiplets.

We present the final report from a series of precision measurements of the muon anomalous magnetic moment, ${a}_{\ensuremath{\mu}}=(g\ensuremath{-}2)/2$. The details of the experimental method, apparatus, data taking, and analysis are summarized. Data obtained at Brookhaven National Laboratory, using nearly equal samples of positive and negative muons, were used to deduce ${a}_{\ensuremath{\mu}}(\mathrm{\text{Expt}})=11659208.0(5.4)(3.3)\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}10}$, where the statistical and systematic uncertainties are given, respectively. The combined uncertainty of 0.54 ppm represents a 14-fold improvement compared to previous measurements at CERN. The standard model value for ${a}_{\ensuremath{\mu}}$ includes contributions from virtual QED, weak, and hadronic processes. While the QED processes account for most of the anomaly, the largest theoretical uncertainty, $\ensuremath{\approx}0.55\text{ }\text{ }\mathrm{ppm}$, is associated with first-order hadronic vacuum polarization. Present standard model evaluations, based on ${e}^{+}{e}^{\ensuremath{-}}$ hadronic cross sections, lie 2.2--2.7 standard deviations below the experimental result.

Dilute magnetic semiconductors and wide gap oxide semiconductors are appealing materials for magnetooptical devices. From a combinatorial screening approach looking at the solid solubility of transition metals in titanium dioxides and of their magnetic properties, we report on the observation of transparent ferromagnetism in cobalt-doped anatase thin films with theconcentration of cobalt between 0 and 8%. Magnetic microscopy images reveal a magnetic domain structure in the films, indicating the existence of ferromagnetic long-range ordering. The materials remain ferromagnetic above room temperature with a magnetic moment of 0.32 Bohr magnetons per cobalt atom. The film is conductive and exhibits a positive magnetoresistance of 60% at 2 kelvin.

Chapter 3 of Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). This chapter addresses changes in weather and climate events relevant to extreme impacts and disasters.

This paper discusses a general approach to quali- tative modeling based on fuzzy logic. The method of qualitative modeling is divided into two parts: fuzzy modeling and linguistic approximation. It proposes to use a fuzzy clustering method (fuzzy c-means method) to identify the structure of a fuzzy model. To clarify the advantages of the proposed method, it also shows some examples of modeling, among them a model of a dynamical process and a model of a human operator's control action.

In regular statistical models, the leave-one-out cross-validation is asymptotically equivalent to the Akaike information criterion. However, since many learning machines are singular statistical models, the asymptotic behavior of the cross-validation remains unknown. In previous studies, we established the singular learning theory and proposed a widely applicable information criterion, the expectation value of which is asymptotically equal to the average Bayes generalization loss. In the present paper, we theoretically compare the Bayes cross-validation loss and the widely applicable information criterion and prove two theorems. First, the Bayes cross-validation loss is asymptotically equivalent to the widely applicable information criterion as a random variable. Therefore, model selection and hyperparameter optimization using these two values are asymptotically equivalent. Second, the sum of the Bayes generalization error and the Bayes cross-validation error is asymptotically equal to $2λ/n$, where $λ$ is the real log canonical threshold and $n$ is the number of training samples. Therefore the relation between the cross-validation error and the generalization error is determined by the algebraic geometrical structure of a learning machine. We also clarify that the deviance information criteria are different from the Bayes cross-validation and the widely applicable information criterion.

We introduce quantum fluctuations into the simulated annealing process of optimization problems, aiming at faster convergence to the optimal state. Quantum fluctuations cause transitions between states and thus play the same role as thermal fluctuations in the conventional approach. The idea is tested by the transverse Ising model, in which the transverse field is a function of time similar to the temperature in the conventional method. The goal is to find the ground state of the diagonal part of the Hamiltonian with high accuracy as quickly as possible. We have solved the time-dependent Schr\"odinger equation numerically for small size systems with various exchange interactions. Comparison with the results of the corresponding classical (thermal) method reveals that the quantum annealing leads to the ground state with much larger probability in almost all cases if we use the same annealing schedule.

This is a corrected printing of the second edition of Lang's well-known textbook. It covers all of the basic material of classical algebraic number theory, giving the student the background necessary for the study of further topics in algebraic number theory, such as cyclotomic fields, or modular forms. Part I introduces some of the basic ideas of the theory: number fields, ideal classes, ideles and adeles, and zeta functions. It also contains a version of a Riemann-Roch theorem in number fields, proved by Lang in the very first version of the book in the sixties. This version can now be seen as a precursor of Arakelov theory. Part II covers class field theory, and Part III is devoted to analytic methods, including an exposition of Tate's thesis, the Brauer-Siegel theorem, and Weil's explicit formulas. The second edition contains corrections, as well as several additions to the previous edition, and the last chapter on explicit formulas has been rewritten.