Tamkang University

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\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,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\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,

Because of their high theoretical energy density and low cost, lithium–sulfur (Li–S) batteries are promising next-generation energy storage devices. The electrochemical performance of Li–S batteries largely depends on the efficient reversible conversion of Li polysulfides to Li2S in discharge and to elemental S during charging. Here, we report on our discovery that monodisperse cobalt atoms embedded in nitrogen-doped graphene (Co–N/G) can trigger the surface-mediated reaction of Li polysulfides. Using a combination of operando X-ray absorption spectroscopy and first-principles calculation, we reveal that the Co–N–C coordination center serves as a bifunctional electrocatalyst to facilitate both the formation and the decomposition of Li2S in discharge and charge processes, respectively. The S@Co–N/G composite, with a high S mass ratio of 90 wt %, can deliver a gravimetric capacity of 1210 mAh g–1, and it exhibits an areal capacity of 5.1 mAh cm–2 with capacity fading rate of 0.029% per cycle over 100 cycles at 0.2 C at S loading of 6.0 mg cm–2 on the electrode disk.

for OER in a dynamic way by observing the surface dynamic evolution process of defective electrocatalysts and identifying the real active sites during the electrocatalysis process. The current finding would motivate the community to focus more on the dynamic behavior of defect electrocatalysts.

Abstract Customer loyalty or repeat purchasing is critical for the survival and success of any store. By focusing on online stores, this study investigates the repeat purchase intention of experienced online buyers based on means‐end chain theory and prospect theory. In the research model, both utilitarian value and hedonic value are hypothesised to affect repeat purchase intention positively. Perceived risk is hypothesised to affect repeat purchase intention negatively and moderate the effects of utilitarian and hedonic values on repeat purchase intention. Utilitarian value is proposed as a formative second‐order construct formed by product offerings, product information, monetary savings and convenience. Hedonic value is also proposed as a formative second‐order construct formed by the six hedonic benefits that have been identified in prior research. Data collected from 782 Yahoo!Kimo customers provide strong support for the research model. The results indicate that both the utilitarian value and hedonic value are positively associated with buyers' repeat purchase intention. A higher level of perceived risk reduces the effect of utilitarian value and increases the effect of hedonic value on repeat purchase intention. Implications for theory and practice and suggestions for future research are provided.

Purpose The purpose of this study is to develop an original framework to explore the influences of green perceived value and green perceived risk on green purchase intentions and to discuss the mediation role of green trust. Design/methodology/approach This study applies four original concepts – green perceived value, green perceived risk, green trust, and green purchase intentions – to develop an integral model to enhance green purchase intentions. In addition, this research employs an empirical study by means of the questionnaire survey method to verify the hypotheses and to explore its managerial implications. Structural equation modeling (SEM) is applied to verify the research framework. Findings The empirical results show that green perceived value would positively affect green trust and green purchase intentions, while green perceived risk would negatively influence both of them. Furthermore, this study demonstrates that the relationships between green purchase intentions and their two antecedents – green perceived value and green perceived risk – are partially mediated by green trust. Hence, investing resources to increase green perceived value and to decrease green perceived risk is helpful to enhance green trust and green purchase intentions. Originality/value This study summarizes the literature on green marketing and relationship marketing into a new managerial framework of green purchase intentions. It utilizes four novel constructs – green perceived value, green perceived risk, green trust, and green purchase intentions – to develop an original research framework to enhance green purchase intentions. Although past research has highlighted the relevant issues about purchase intentions, none explores it about green management. Therefore, this paper develops the research framework of green purchase intentions to fill the research gap.

It is of essential importance to design an electrocatalyst with excellent performance for both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in water splitting.

Designing atomically dispersed metal catalysts for oxygen reduction reaction (ORR) is a promising approach to achieve efficient energy conversion. Herein, we develop a template-assisted method to synthesize a series of single metal atoms anchored on porous N,S-codoped carbon (NSC) matrix as highly efficient ORR catalysts to investigate the correlation between the structure and their catalytic performance. The structure analysis indicates that an identical synthesis method results in distinguished structural differences between Fe-centered single-atom catalyst (Fe-SAs/NSC) and Co-centered/Ni-centered single-atom catalysts (Co-SAs/NSC and Ni-SAs/NSC) because of the different trends of each metal ion in forming a complex with the N,S-containing precursor during the initial synthesis process. The Fe-SAs/NSC mainly consists of a well-dispersed FeN4S2 center site where S atoms form bonds with the N atoms. The S atoms in Co-SAs/NSC and Ni-SAs/NSC, on the other hand, form metal–S bonds, resulting in CoN3S1 and NiN3S1 center sites. Density functional theory (DFT) reveals that the FeN4S2 center site is more active than the CoN3S1 and NiN3S1 sites, due to the higher charge density, lower energy barriers of the intermediates, and products involved. The experimental results indicate that all three single-atom catalysts could contribute high ORR electrochemical performances, while Fe-SAs/NSC exhibits the highest of all, which is even better than commercial Pt/C. Furthermore, Fe-SAs/NSC also displays high methanol tolerance as compared to commercial Pt/C and high stability up to 5000 cycles. This work provides insights into the rational design of the definitive structure of single-atom catalysts with tunable electrocatalytic activities for efficient energy conversion.

Abstract Electronic structure greatly determines the band structures and the charge carrier transport properties of semiconducting photocatalysts and consequently their photocatalytic activities. Here, by simply calcining the mixture of graphitic carbon nitride (g‐C 3 N 4 ) and sodium borohydride in an inert atmosphere, boron dopants and nitrogen defects are simultaneously introduced into g‐C 3 N 4 . The resultant boron‐doped and nitrogen‐deficient g‐C 3 N 4 exhibits excellent activity for photocatalytic oxygen evolution, with highest oxygen evolution rate reaching 561.2 µmol h −1 g −1 , much higher than previously reported g‐C 3 N 4 . It is well evidenced that with conduction and valence band positions substantially and continuously tuned by the simultaneous introduction of boron dopants and nitrogen defects into g‐C 3 N 4 , the band structures are exceptionally modulated for both effective optical absorption in visible light and much increased driving force for water oxidation. Moreover, the engineered electronic structure creates abundant unsaturated sites and induces strong interlayer C–N interaction, leading to efficient electron excitation and accelerated charge transport. In the present work, a facile approach is successfully demonstrated to engineer the electronic structures and the band structures of g‐C 3 N 4 with simultaneous introduction of dopants and defects for high‐performance photocatalytic oxygen evolution, which can provide informative principles for the design of efficient photocatalysis systems for solar energy conversion.

We report on the population properties of compact binary mergers inferred from gravitational-wave observations of these systems during the first three LIGO-Virgo observing runs. The Gravitational-Wave Transient Catalog 3 (GWTC-3) contains signals consistent with three classes of binary mergers: binary black hole, binary neutron star, and neutron star–black hole mergers. We infer the binary neutron star merger rate to be between 10 and <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mrow><a:mn>1700</a:mn><a:mtext> </a:mtext><a:mtext> </a:mtext><a:msup><a:mrow><a:mi>Gpc</a:mi></a:mrow><a:mrow><a:mo>−</a:mo><a:mn>3</a:mn></a:mrow></a:msup><a:mtext> </a:mtext><a:msup><a:mrow><a:mi>yr</a:mi></a:mrow><a:mrow><a:mo>−</a:mo><a:mn>1</a:mn></a:mrow></a:msup></a:mrow></a:math> and the neutron star–black hole merger rate to be between 7.8 and <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"><c:mrow><c:mn>140</c:mn><c:mtext> </c:mtext><c:mtext> </c:mtext><c:msup><c:mrow><c:mi>Gpc</c:mi></c:mrow><c:mrow><c:mo>−</c:mo><c:mn>3</c:mn></c:mrow></c:msup><c:mtext> </c:mtext><c:msup><c:mrow><c:mi>yr</c:mi></c:mrow><c:mrow><c:mo>−</c:mo><c:mn>1</c:mn></c:mrow></c:msup></c:mrow></c:math>, assuming a constant rate density in the comoving frame and taking the union of 90% credible intervals for methods used in this work. We infer the binary black hole merger rate, allowing for evolution with redshift, to be between 17.9 and <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"><e:mrow><e:mn>44</e:mn><e:mtext> </e:mtext><e:mtext> </e:mtext><e:msup><e:mrow><e:mi>Gpc</e:mi></e:mrow><e:mrow><e:mo>−</e:mo><e:mn>3</e:mn></e:mrow></e:msup><e:mtext> </e:mtext><e:msup><e:mrow><e:mi>yr</e:mi></e:mrow><e:mrow><e:mo>−</e:mo><e:mn>1</e:mn></e:mrow></e:msup></e:mrow></e:math> at a fiducial redshift (<g:math xmlns:g="http://www.w3.org/1998/Math/MathML" display="inline"><g:mi>z</g:mi><g:mo>=</g:mo><g:mn>0.2</g:mn></g:math>). The rate of binary black hole mergers is observed to increase with redshift at a rate proportional to <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" display="inline"><i:mo stretchy="false">(</i:mo><i:mn>1</i:mn><i:mo>+</i:mo><i:mi>z</i:mi><i:msup><i:mo stretchy="false">)</i:mo><i:mi>κ</i:mi></i:msup></i:math> with <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"><m:mi>κ</m:mi><m:mo>=</m:mo><m:mn>2.</m:mn><m:msubsup><m:mn>9</m:mn><m:mrow><m:mo>−</m:mo><m:mn>1.8</m:mn></m:mrow><m:mrow><m:mo>+</m:mo><m:mn>1.7</m:mn></m:mrow></m:msubsup></m:math> for <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" display="inline"><o:mi>z</o:mi><o:mo>≲</o:mo><o:mn>1</o:mn></o:math>. Using both binary neutron star and neutron star–black hole binaries, we obtain a broad, relatively flat neutron star mass distribution extending from <q:math xmlns:q="http://www.w3.org/1998/Math/MathML" display="inline"><q:msubsup><q:mn>1.2</q:mn><q:mrow><q:mo>−</q:mo><q:mn>0.2</q:mn></q:mrow><q:mrow><q:mo>+</q:mo><q:mn>0.1</q:mn></q:mrow></q:msubsup></q:math> to <s:math xmlns:s="http://www.w3.org/1998/Math/MathML" display="inline"><s:msubsup><s:mn>2.0</s:mn><s:mrow><s:mo>−</s:mo><s:mn>0.3</s:mn></s:mrow><s:mrow><s:mo>+</s:mo><s:mn>0.3</s:mn></s:mrow></s:msubsup><s:msub><s:mi>M</s:mi><s:mo stretchy="false">⊙</s:mo></s:msub></s:math>. We confidently determine that the merger rate as a function of mass sharply declines after the expected maximum neutron star mass, but cannot yet confirm or rule out the existence of a lower mass gap between neutron stars and black holes. We also find the binary black hole mass distribution has localized over- and underdensities relative to a power-law distribution, with peaks emerging at chirp masses of <v:math xmlns:v="http://www.w3.org/1998/Math/MathML" display="inline"><v:msubsup><v:mn>8.3</v:mn><v:mrow><v:mo>−</v:mo><v:mn>0.5</v:mn></v:mrow><v:mrow><v:mo>+</v:mo><v:mn>0.3</v:mn></v:mrow></v:msubsup></v:math> and <x:math xmlns:x="http://www.w3.org/1998/Math/MathML" display="inline"><x:msubsup><x:mn>27.9</x:mn><x:mrow><x:mo>−</x:mo><x:mn>1.8</x:mn></x:mrow><x:mrow><x:mo>+</x:mo><x:mn>1.9</x:mn></x:mrow></x:msubsup><x:msub><x:mi>M</x:mi><x:mo stretchy="false">⊙</x:mo></x:msub></x:math>. While we continue to find that the mass distribution of a binary’s more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above approximately <ab:math xmlns:ab="http://www.w3.org/1998/Math/MathML" display="inline"><ab:mn>60</ab:mn><ab:msub><ab:mi>M</ab:mi><ab:mo stretchy="false">⊙</ab:mo></ab:msub></ab:math>, which would indicate the presence of a upper mass gap. Observed black hole spins are small, with half of spin magnitudes below <db:math xmlns:db="http://www.w3.org/1998/Math/MathML" display="inline"><db:msub><db:mi>χ</db:mi><db:mi>i</db:mi></db:msub><db:mo>≈</db:mo><db:mn>0.25</db:mn></db:math>. While the majority of spins are preferentially aligned with the orbital angular momentum, we infer evidence of antialigned spins among the binary population. We observe an increase in spin magnitude for systems with more unequal-mass ratio. We also observe evidence of misalignment of spins relative to the orbital angular momentum. Published by the American Physical Society 2023

A connection to nature index was developed and tested to measure children’s affective attitude toward the natural environment. The index was employed through a survey that investigates students’ attitude toward Lagoon Quest, a mandatory environmental education program for all fourth-grade, public school students in Brevard County, Florida. Factor analyses were conducted to explore and confirm different factors in the connection to nature index. A path analysis was conducted to examine the association among variables. The results suggest four dimensions in the children’s connection to nature index: (a) enjoyment of nature, (b) empathy for creatures, (c) sense of oneness, and (d) sense of responsibility. Children’s connection to nature influences their intention to participate in nature-based activities in the future. Children’s connection to nature, their previous experience in nature, their perceived family value toward nature, and their perceived control positively influenced their interest in performing environmentally friendly behaviors.

This research investigates the relationships between knowledge sharing, absorptive capacity, and innovation capability in Taiwan's knowledge-intensive industries. We propose statistical hypotheses and a LISREL model to study these based on the data sampled from 170 Taiwanese firms, including electronic, financial insurance and medical industries, yielding 355 valid returned research samples. By testing three hypotheses, this study finds that absorptive capacity is the intervening factor between knowledge sharing and innovation capability. It also shows that knowledge sharing has a positive effect on absorptive capacity, and that a completely mediating model exhibits both model generalization and extension characteristics through multiple model comparison in different industry population samples. Finally, managerial implications are discussed and a brief conclusion is presented.

We report the observation of gravitational waves from two compact binary coalescences in LIGO's and Virgo's third observing run with properties consistent with neutron star-black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO-Virgo detectors. The source of GW200105 has component masses, whereas the source of GW200115 has component masses and (all measurements quoted at the 90% credible level). The probability that the secondary's mass is below the maximal mass of a neutron star is 89%-96% and 87%-98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are and, respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of when assuming that GW200105 and GW200115 are representative of the NSBH population or under the assumption of a broader distribution of component masses. © 2021. The Author(s). Published by the American Astronomical Society.

An overview of new and current developments in state of charge (SOC) estimating methods for battery is given where the focus lies upon mathematical principles and practical implementations. As the battery SOC is an important parameter, which reflects the battery performance, so accurate estimation of SOC cannot only protect battery, prevent overcharge or discharge, and improve the battery life, but also let the application make rationally control strategies to achieve the purpose of saving energy. This paper gives a literature survey on the categories and mathematical methods of SOC estimation. Based on the assessment of SOC estimation methods, the future development direction of SOC estimation is proposed.

Abstract The development of oxygen reduction reaction (ORR) electrocatalysts based on earth‐abundant nonprecious materials is critically important for sustainable large‐scale applications of fuel cells and metal–air batteries. Herein, a hetero‐single‐atom (h‐SA) ORR electrocatalyst is presented, which has atomically dispersed Fe and Ni coanchored to a microsized nitrogen‐doped graphitic carbon support with unique trimodal‐porous structure configured by highly ordered macropores interconnected through mesopores. Extended X‐ray absorption fine structure spectra confirm that Fe‐ and Ni‐SAs are affixed to the carbon support via FeN 4 and NiN 4 coordination bonds. The resultant Fe/Ni h‐SA electrocatalyst exhibits an outstanding ORR activity, outperforming SA electrocatalysts with only Fe‐ or Ni‐SAs, and the benchmark Pt/C. The obtained experimental results indicate that the achieved outstanding ORR performance results from the synergetic enhancement induced by the coexisting FeN 4 and NiN 4 sites, and the superior mass‐transfer capability promoted by the trimodal‐porous‐structured carbon support.

Understanding the role of the oxidation state of the Cu surface and surface-adsorbed intermediate species in electrochemical CO2 reduction is crucial for the development of selective CO2-to-fuel electrocatalysts. In this study, the electrochemical CO2 reduction mechanism over the Cu catalysts with various oxidation states was studied by using in situ surface-enhanced infrared absorption spectroscopy (SEIRAS), in situ soft X-ray absorption spectroscopy (Cu L-edge), and online gas chromatography measurements. The atop-adsorbed CO (COatop) intermediate is obtained on the electrodeposited Cu surface which primarily has the oxidation state of Cu(I). COatop is further reduced, followed by the formation of C1 product such as CH4. The residual bridge-adsorbed CO (CObridge) is formed on the as-prepared Cu surface with Cu(0) which inhibits hydrocarbon formation. In contrast, the CV-treated Cu electrode prepared by oxidizing the as-prepared Cu surface contains different amounts of Cu(I) and Cu(0) states. The major theme of this work is that in situ SEIRAS results show the coexistence of COatop and CObridge as the reaction intermediates during CO2 reduction and that the selectivity of CO2-to-ethylene conversion is further enhanced in the CV-treated Cu electrode. The Cu catalysts modulated by the electrochemical method exhibit different oxidation states and reaction intermediates as well as electrocatalytic properties.

OBJECTIVE: The aim of this study was to develop a self-administered scale based on the special features of smartphone. The reliability and validity of the Smartphone Addiction Inventory (SPAI) was demonstrated. METHODS: A total of 283 participants were recruited from Dec. 2012 to Jul. 2013 to complete a set of questionnaires, including a 26-item SPAI modified from the Chinese Internet Addiction Scale and phantom vibration and ringing syndrome questionnaire. There were 260 males and 23 females, with ages 22.9 ± 2.0 years. Exploratory factor analysis, internal-consistency test, test-retest, and correlation analysis were conducted to verify the reliability and validity of the SPAI. Correlations between each subscale and phantom vibration and ringing were also explored. RESULTS: Exploratory factor analysis yielded four factors: compulsive behavior, functional impairment, withdrawal and tolerance. Test-retest reliabilities (intraclass correlations = 0.74-0.91) and internal consistency (Cronbach's α = 0.94) were all satisfactory. The four subscales had moderate to high correlations (0.56-0.78), but had no or very low correlation to phantom vibration/ringing syndrome. CONCLUSION: This study provides evidence that the SPAI is a valid and reliable, self-administered screening tool to investigate smartphone addiction. Phantom vibration and ringing might be independent entities of smartphone addiction.

Electronic structure calculations of $\ensuremath{\beta}\ensuremath{-}{\mathrm{BaB}}_{2}{\mathrm{O}}_{4}$ from first principles are performed based on a plane-wave pseudopotential method, and the linear optical properties are then obtained. The static second-harmonic generation (SHG) coefficients are calculated at the independent-particle level with a formalism originally given by Aversa and Sipe [Phys. Rev. B 52, 14 636 (1995)] and later rearranged by Rashkeev et al. [Phys. Rev. B 57, 3905 (1998)] to explicitly show Kleinman's symmetry. The formalism is improved to be more efficient in reducing the $k$ points necessary for convergence. A real-space atom-cutting method is suggested to analyze the respective contributions of various transitions among ions and ion groups to optical response. The contribution of the cation Ba to SHG effects is found to be not important but non-negligible, while its contribution to birefringence is negligible.

Engineering phosphorous anodes A focus of battery research has been the development of a range of lithium, sodium, and potassium cathodes, but improving anode materials is also an important goal. Silicon has shown some promise for replacing graphite because of its exceptional capacity, but the dramatic volume change during lithiation-delithiation processes often leads to failure. Jin et al. developed a composite that is made of black phosphorous and graphite in its core and covered with swollen polyaniline. In contrast to previous efforts, bonding between the carbon and phosphorous allows for a high charging rate without sacrifices in capacity and cycling stability. Science , this issue p. 192

A 16-nation study involving 8,360 participants revealed that hostile and benevolent attitudes toward men, assessed by the Ambivalence Toward Men Inventory (P. Click & S.T. Fiske, 1999), were (a) reliably measured across cultures, (b) positively correlated (for men and women, within samples and across nations) with each other and with hostile and benevolent sexism toward women (Ambivalent Sexism Inventory, P. Click & S.T. Fiske, 1996), and (c) negatively correlated with gender equality in cross-national comparisons. Stereotype measures indicated that men were viewed as having less positively valenced but more powerful traits than women. The authors argue that hostile as well as benevolent attitudes toward men reflect and support gender inequality by characterizing men as being designed for dominance.

The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website.