Universität Hamburg

Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these approaches do not reliably detect the lack of discriminant validity in common research situations. We therefore propose an alternative approach, based on the multitrait-multimethod matrix, to assess discriminant validity: the heterotrait-monotrait ratio of correlations. We demonstrate its superior performance by means of a Monte Carlo simulation study, in which we compare the new approach to the Fornell-Larcker criterion and the assessment of (partial) cross-loadings. Finally, we provide guidelines on how to handle discriminant validity issues in variance-based structural equation modeling.

Purpose The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power and the need for goodness-of-fit testing. Next, the metrics as well as the rules of thumb that should be applied to assess the PLS-SEM results are covered. Besides presenting established PLS-SEM evaluation criteria, the overview includes the following new guidelines: PLSpredict (i.e., a novel approach for assessing a model’s out-of-sample prediction), metrics for model comparisons, and several complementary methods for checking the results’ robustness. Design/methodology/approach This paper provides an overview of previously and recently proposed metrics as well as rules of thumb for evaluating the research results based on the application of PLS-SEM. Findings Most of the previously applied metrics for evaluating PLS-SEM results are still relevant. Nevertheless, scholars need to be knowledgeable about recently proposed metrics (e.g. model comparison criteria) and methods (e.g. endogeneity assessment, latent class analysis and PLSpredict), and when and how to apply them to extend their analyses. Research limitations/implications Methodological developments associated with PLS-SEM are rapidly emerging. The metrics reported in this paper are useful for current applications, but must always be up to date with the latest developments in the PLS-SEM method. Originality/value In light of more recent research and methodological developments in the PLS-SEM domain, guidelines for the method’s use need to be continuously extended and updated. This paper is the most current and comprehensive summary of the PLS-SEM method and the metrics applied to assess its solutions.

On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of 1.0×10(-21). It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203,000 years, equivalent to a significance greater than 5.1σ. The source lies at a luminosity distance of 410(-180)(+160) Mpc corresponding to a redshift z=0.09(-0.04)(+0.03). In the source frame, the initial black hole masses are 36(-4)(+5)M⊙ and 29(-4)(+4)M⊙, and the final black hole mass is 62(-4)(+4)M⊙, with 3.0(-0.5)(+0.5)M⊙c(2) radiated in gravitational waves. All uncertainties define 90% credible intervals. These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

Reconstructing phylogenies from intraspecific data (such as human mitochondrial DNA variation) is often a challenging task because of large sample sizes and small genetic distances between individuals. The resulting multitude of plausible trees is best expressed by a network which displays alternative potential evolutionary paths in the form of cycles. We present a method ("median joining" [MJ]) for constructing networks from recombination-free population data that combines features of Kruskal's algorithm for finding minimum spanning trees by favoring short connections, and Farris's maximum-parsimony (MP) heuristic algorithm, which sequentially adds new vertices called "median vectors", except that our MJ method does not resolve ties. The MJ method is hence closely related to the earlier approach of Foulds, Hendy, and Penny for estimating MP trees but can be adjusted to the level of homoplasy by setting a parameter epsilon. Unlike our earlier reduced median (RM) network method, MJ is applicable to multistate characters (e.g., amino acid sequences). An additional feature is the speed of the implemented algorithm: a sample of 800 worldwide mtDNA hypervariable segment I sequences requires less than 3 h on a Pentium 120 PC. The MJ method is demonstrated on a Tibetan mitochondrial DNA RFLP data set.

The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles ("MISEV") guidelines for the field in 2014. We now update these "MISEV2014" guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.

On August 17, 2017 at 12∶41:04 UTC the Advanced LIGO and Advanced Virgo gravitational-wave detectors made their first observation of a binary neutron star inspiral. The signal, GW170817, was detected with a combined signal-to-noise ratio of 32.4 and a false-alarm-rate estimate of less than one per <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mrow><a:mrow><a:mn>8.0</a:mn><a:mo>×</a:mo><a:msup><a:mrow><a:mn>10</a:mn></a:mrow><a:mrow><a:mn>4</a:mn></a:mrow></a:msup></a:mrow><a:mtext> </a:mtext><a:mtext> </a:mtext><a:mi>years</a:mi></a:mrow></a:math>. We infer the component masses of the binary to be between 0.86 and <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"><c:mrow><c:mn>2.26</c:mn><c:mtext> </c:mtext><c:mtext> </c:mtext><c:msub><c:mrow><c:mi>M</c:mi></c:mrow><c:mrow><c:mo stretchy="false">⊙</c:mo></c:mrow></c:msub></c:mrow></c:math>, in agreement with masses of known neutron stars. Restricting the component spins to the range inferred in binary neutron stars, we find the component masses to be in the range <f:math xmlns:f="http://www.w3.org/1998/Math/MathML" display="inline"><f:mrow><f:mn>1.17</f:mn><f:mi>–</f:mi><f:mn>1.60</f:mn><f:mtext> </f:mtext><f:mtext> </f:mtext><f:msub><f:mrow><f:mi>M</f:mi></f:mrow><f:mrow><f:mo stretchy="false">⊙</f:mo></f:mrow></f:msub></f:mrow></f:math>, with the total mass of the system <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" display="inline"><i:mrow><i:mn>2.7</i:mn><i:msubsup><i:mrow><i:mn>4</i:mn></i:mrow><i:mrow><i:mo>−</i:mo><i:mn>0.01</i:mn></i:mrow><i:mrow><i:mo>+</i:mo><i:mn>0.04</i:mn></i:mrow></i:msubsup><i:msub><i:mrow><i:mi>M</i:mi></i:mrow><i:mrow><i:mo stretchy="false">⊙</i:mo></i:mrow></i:msub></i:mrow></i:math>. The source was localized within a sky region of <l:math xmlns:l="http://www.w3.org/1998/Math/MathML" display="inline"><l:mrow><l:mn>28</l:mn><l:mtext> </l:mtext><l:mtext> </l:mtext><l:mrow><l:msup><l:mrow><l:mi>deg</l:mi></l:mrow><l:mrow><l:mn>2</l:mn></l:mrow></l:msup></l:mrow></l:mrow></l:math> (90% probability) and had a luminosity distance of <n:math xmlns:n="http://www.w3.org/1998/Math/MathML" display="inline"><n:mrow><n:mrow><n:mn>4</n:mn><n:msubsup><n:mrow><n:mn>0</n:mn></n:mrow><n:mrow><n:mo>−</n:mo><n:mn>14</n:mn></n:mrow><n:mrow><n:mo>+</n:mo><n:mn>8</n:mn></n:mrow></n:msubsup><n:mtext> </n:mtext><n:mtext> </n:mtext></n:mrow><n:mrow><n:mi>Mpc</n:mi></n:mrow></n:mrow></n:math>, the closest and most precisely localized gravitational-wave signal yet. The association with the <p:math xmlns:p="http://www.w3.org/1998/Math/MathML" display="inline"><p:mi>γ</p:mi></p:math>-ray burst GRB 170817A, detected by Fermi-GBM 1.7 s after the coalescence, corroborates the hypothesis of a neutron star merger and provides the first direct evidence of a link between these mergers and short <r:math xmlns:r="http://www.w3.org/1998/Math/MathML" display="inline"><r:mi>γ</r:mi></r:math>-ray bursts. Subsequent identification of transient counterparts across the electromagnetic spectrum in the same location further supports the interpretation of this event as a neutron star merger. This unprecedented joint gravitational and electromagnetic observation provides insight into astrophysics, dense matter, gravitation, and cosmology. Published by the American Physical Society 2017

Recent years have seen a rapid proliferation of mass-market consumer software that takes inspiration from video games. Usually summarized as "gamification", this trend connects to a sizeable body of existing concepts and research in human-computer interaction and game studies, such as serious games, pervasive games, alternate reality games, or playful design. However, it is not clear how "gamification" relates to these, whether it denotes a novel phenomenon, and how to define it. Thus, in this paper we investigate "gamification" and the historical origins of the term in relation to precursors and similar concepts. It is suggested that "gamified" applications provide insight into novel, gameful phenomena complementary to playful phenomena. Based on our research, we propose a definition of "gamification" as the use of game design elements in non-game contexts.

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,873 new measurements from 758 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 118 reviews are many that are new or heavily revised, including a new review on Neutrinos in Cosmology.Starting with this edition, the Review is divided into two volumes. Volume 1 includes the Summary Tables and all review articles. Volume 2 consists of the Particle Listings. Review articles that were previously part of the Listings are now included in volume 1.The complete Review (both volumes) is published online on the website of the Particle Data Group (http://pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is also available.The 2018 edition of the Review of Particle Physics should be cited as: M. Tanabashi et al. (Particle Data Group), Phys. Rev. D 98, 030001 (2018).

Gaia is a cornerstone mission in the science programme of the EuropeanSpace Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page.

This biennial Review summarizes much of particle physics. Using data from previous editions, plus 2658 new measurements from 644 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors, probability, and statistics. Among the 112 reviews are many that are new or heavily revised including those on Heavy-Quark and Soft-Collinear Effective Theory, Neutrino Cross Section Measurements, Monte Carlo Event Generators, Lattice QCD, Heavy Quarkonium Spectroscopy, Top Quark, Dark Matter, ${V}_{\mathit{cb}}$ ${V}_{\mathit{ub}}$, Quantum Chromodynamics, High-Energy Collider Parameters, Astrophysical Constants, Cosmological Parameters, and Dark Matter.A booklet is available containing the Summary Tables and abbreviated versions of some of the other sections of this full Review. All tables, listings, and reviews (and errata) are also available on the Particle Data Group website: http://pdg.lbl.gov/.The 2012 edition of Review of Particle Physics is published for the Particle Data Group as article 010001 in volume 86 of Physical Review D.This edition should be cited as: J. Beringer et al. (Particle Data Group), Phys. Rev. D 86, 010001 (2012).

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,&#13;\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,&#13;\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,&#13;\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,&#13;\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,&#13;\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,&#13;\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,&#13;\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,&#13;\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,&#13;\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,&#13;\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,&#13;\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,&#13;\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,&#13;\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,&#13;\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,&#13;\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,&#13;\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,&#13;\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,&#13;\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,&#13;\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,&#13;\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,&#13;\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,&#13;\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,&#13;\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,&#13;\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,&#13;\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,&#13;\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,&#13;\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,&#13;\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,&#13;\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,&#13;\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,&#13;\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,&#13;\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,&#13;\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,&#13;\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,&#13;\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,&#13;\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,&#13;\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,&#13;\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,&#13;\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,&#13;\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,&#13;\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,&#13;\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,&#13;\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,&#13;\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,&#13;\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,&#13;\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,&#13;\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,&#13;\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,&#13;\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,&#13;\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,&#13;\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,&#13;\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,&#13;\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,&#13;\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,&#13;\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,&#13;\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,&#13;\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,&#13;\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,&#13;\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,&#13;\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,&#13;\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,&#13;\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,&#13;\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,&#13;\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,&#13;\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,&#13;\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,&#13;\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,&#13;\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,&#13;\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,&#13;\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,&#13;\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,&#13;\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,&#13;\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,&#13;\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,&#13;\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,&#13;\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,&#13;\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,&#13;\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,&#13;\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,&#13;\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,&#13;\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,&#13;\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,&#13;\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,&#13;\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,&#13;\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

The newest version of MUMmer easily handles comparisons of large eukaryotic genomes at varying evolutionary distances, as demonstrated by applications to multiple genomes. Two new graphical viewing tools provide alternative ways to analyze genome alignments. The new system is the first version of MUMmer to be released as open-source software. This allows other developers to contribute to the code base and freely redistribute the code. The MUMmer sources are available at http://www.tigr.org/software/mummer.

The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 1034 cm−2 s−1 (1027 cm−2 s−1). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4π solid angle. Forward sampling calorimeters extend the pseudorapidity coverage to high values (|η| ≤ 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

This article works out the main characteristics of `practice theory', a type of social theory which has been sketched by such authors as Bourdieu, Giddens, Taylor, late Foucault and others. Practice theory is presented as a conceptual alternative to other forms of social and cultural theory, above all to culturalist mentalism, textualism and intersubjectivism. The article shows how practice theory and the three other cultural-theoretical vocabularies differ in their localization of the social and in their conceptualization of the body, mind, things, knowledge, discourse, structure/process and the agent.

Abstract The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,324 new measurements from 878 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on High Energy Soft QCD and Diffraction and one on the Determination of CKM Angles from B Hadrons. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 98 review articles. Volume 2 consists of the Particle Listings and contains also 22 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print and as a web version optimized for use on phones as well as an Android app.

A crucial part of statistical analysis is evaluating a model's quality and fit, or performance. During analysis, especially with regression models, investigating the fit of models to data also often involves selecting the best fitting model amongst many competing models. Upon investigation, fit indices should also be reported both visually and numerically to bring readers in on the investigative effort.

BACKGROUND: The 7-item Generalized Anxiety Disorder Scale (GAD-7) is a practical self-report anxiety questionnaire that proved valid in primary care. However, the GAD-7 was not yet validated in the general population and thus far, normative data are not available. OBJECTIVES: To investigate reliability, construct validity, and factorial validity of the GAD-7 in the general population and to generate normative data. RESEARCH DESIGN: Nationally representative face-to-face household survey conducted in Germany between May 5 and June 8, 2006. SUBJECTS: Five thousand thirty subjects (53.6% female) with a mean age (SD) of 48.4 (18.0) years. MEASURES: The survey questionnaire included the GAD-7, the 2-item depression module from the Patient Health Questionnaire (PHQ-2), the Rosenberg Self-Esteem Scale, and demographic characteristics. RESULTS: Confirmatory factor analyses substantiated the 1-dimensional structure of the GAD-7 and its factorial invariance for gender and age. Internal consistency was identical across all subgroups (alpha = 0.89). Intercorrelations with the PHQ-2 and the Rosenberg Self-Esteem Scale were r = 0.64 (P < 0.001) and r = -0.43 (P < 0.001), respectively. As expected, women had significantly higher mean (SD) GAD-7 anxiety scores compared with men [3.2 (3.5) vs. 2.7 (3.2); P < 0.001]. Normative data for the GAD-7 were generated for both genders and different age levels. Approximately 5% of subjects had GAD-7 scores of 10 or greater, and 1% had GAD-7 scores of 15 or greater. CONCLUSIONS: Evidence supports reliability and validity of the GAD-7 as a measure of anxiety in the general population. The normative data provided in this study can be used to compare a subject's GAD-7 score with those determined from a general population reference group.

The monoclonal antibody Ki-67 detects a nuclear antigen that is present only in proliferating cells. The aim of the present investigation was to clarify whether the Ki-67 nuclear antigen is restricted in its expression to certain phases of the cell cycle. All experiments consistently showed that the Ki-67 nuclear antigen is present in S, G2, and M phase, but is absent in G0. However, the results concerning Ki-67 antigen expression in G1 phase varied: cells passing the early events of mitogen triggered transition from G0 to G1, i.e., G1T and first G1A, lacked the Ki-67 nuclear antigen, whereas G1 cells after mitosis were constantly Ki-67-positive. This result suggests that after mitosis cells might not follow the same metabolic pathways as G0 cells do when entering G1 for the first time. Therefore, we suggest that the early stages of mitogen stimulation represent initial sequences of proliferation and not parts of the cell cycle. Because our data show that the Ki-67 nuclear antigen is present throughout the cell cycle, immunostaining with monoclonal antibody Ki-67 provides a reliable means of rapidly evaluating the growth fraction of normal and neoplastic human cell populations.

The search for a relation between environmental, social, and governance (ESG) criteria and corporate financial performance (CFP) can be traced back to the beginning of the 1970s. Scholars and investors have published more than 2000 empirical studies and several review studies on this relation since then. The largest previous review study analyzes just a fraction of existing primary studies, making findings difficult to generalize. Thus, knowledge on the financial effects of ESG criteria remains fragmented. To overcome this shortcoming, this study extracts all provided primary and secondary data of previous academic review studies. Through doing this, the study combines the findings of about 2200 individual studies. Hence, this study is by far the most exhaustive overview of academic research on this topic and allows for generalizable statements. The results show that the business case for ESG investing is empirically very well founded. Roughly 90% of studies find a nonnegative ESG--CFP relation. More importantly, the large majority of studies reports positive findings. We highlight that the positive ESG impact on CFP appears stable over time. Promising results are obtained when differentiating for portfolio and nonportfolio studies, regions, and young asset classes for ESG investing such as emerging markets, corporate bonds, and green real estate.

High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth's land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979-2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better.