Seoul National University of Science and Technology

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,

Doil Choi and colleagues report the genome sequence of the hot pepper, Capsicum annuum, as well as the resequencing of two cultivated peppers and a wild species, Capsicum chinense. Comparative genomic analysis across Solanaceae provides insights into genome expansion, pungency, ripening and disease resistance in hot peppers. Hot pepper (Capsicum annuum), one of the oldest domesticated crops in the Americas, is the most widely grown spice crop in the world. We report whole-genome sequencing and assembly of the hot pepper (Mexican landrace of Capsicum annuum cv. CM334) at 186.6× coverage. We also report resequencing of two cultivated peppers and de novo sequencing of the wild species Capsicum chinense. The genome size of the hot pepper was approximately fourfold larger than that of its close relative tomato, and the genome showed an accumulation of Gypsy and Caulimoviridae family elements. Integrative genomic and transcriptomic analyses suggested that change in gene expression and neofunctionalization of capsaicin synthase have shaped capsaicinoid biosynthesis. We found differential molecular patterns of ripening regulators and ethylene synthesis in hot pepper and tomato. The reference genome will serve as a platform for improving the nutritional and medicinal values of Capsicum species.

To express the antioxidant capacity of plant foods in a more familiar and easily understood manner (equivalent to vitamin C mg/100 g), two stable radical species, ABTS(*)(-) and DPPH(*), commonly used for antioxidant activity measurements, were employed independently to evaluate their efficacies using apple polyphenolic extracts and seven polyphenolic standards including synthetic Trolox. Their antioxidant activities were expressed as vitamin C equivalent antioxidant capacity (VCEAC) in mg/100 g apple or mg/100 mL of the reference chemical compounds in 10 and 30 min using the ABTS(*)(-) and DPPH(*) scavenging assays, respectively. The antioxidant capacity of Gala apples and seven phenolic standards, determined by both ABTS(*)(-) and DPPH(*) scavenging assays, showed a dose-response of the first-order. Fresh Gala apples had a VCEAC of 205.4 +/- 5.6 mg/100 g using the ABTS assay, and the relative VCEACs of phenolic standards were as follows: gallic acid > quercetin > epicatechin > catechin > vitamin C > rutin > chlorogenic acid > Trolox. With the DPPH radical assay, the VCEAC of fresh Gala apples was 136.0 +/- 6.6 mg/100 g, and the relative VCEACs of seven phenolic standards were, in decreasing order, as follows: gallic acid > quercetin > epicatechin > catechin > or = vitamin C > Trolox > rutin > chlorogenic acid. Because the ABTS assay can be used in both organic and aqueous solvent systems, employs a specific absorbance at a wavelength remote from the visible region, and requires a short reaction time, it is a more desirable method than the DPPH assay. Therefore, it is recommended that antioxidant capacity be expressed as vitamin C mg/100 g equivalent (VCEAC) using the ABTS assay.

Cellulose nanocrystals (CNCs), produced by the acid hydrolysis of wood, cotton or other cellulose-rich sources, constitute a renewable nanosized raw material with a broad range of envisaged uses: for example, in composites, cosmetics and medical devices. The intriguing ability of CNCs to self-organize into a chiral nematic (cholesteric) liquid crystal phase with a helical arrangement has attracted significant interest, resulting in much research effort, as this arrangement gives dried CNC films a photonic band gap. The films thus acquire attractive optical properties, creating possibilities for use in applications such as security papers and mirrorless lasing. In this critical review, we discuss the sensitive balance between glass formation and liquid crystal self-assembly that governs the formation of the desired helical structure. We show that several as yet unclarified observations—some constituting severe obstacles for applications of CNCs—may result from competition between the two phenomena. Moreover, by comparison with the corresponding self-assembly processes of other rod-like nanoparticles, for example, carbon nanotubes and fd virus particles, we outline how further liquid crystal ordering phenomena may be expected from CNCs if the suspension parameters can be better controlled. Alternative interpretations of some unexpected phenomena are provided, and topics for future research are identified, as are new potential application strategies. Cellulose, a renewable biopolymer used throughout history, in particular to make clothing and paper, has recently attracted the interest of materials scientists in its nanocrystalline form. These nanofibers — produced by the acid hydrolysis of for instance cotton or wood — show promise for use in composites, cosmetics and medical devices. A Sweden-South Korea-based team led by Jan Lagerwall and Lennart Bergström now review the self-assembly of cellulose nanocrystals into a “chiral nematic” liquid-crystalline phase, which exhibits long-range ordering and adopts a helical superstructure. They compare the behavior of nanocellulose to other rod-like nanoparticles, such as nanotubes, and discuss the competitive gelation that can occur, which yields a glassy — rather than liquid-crystalline — phase. Through its chiral nematic arrangement, nanocellulose is endowed with interesting mechanical and optical properties. Furthermore, its liquid-crystalline suspensions can be processed into thin films, whose development and potential applications are discussed. The chiral liquid crystalline self-organization of cellulose nanocrystals into helical arrangements, giving the resulting materials photonic crystal properties and enhanced mechanical behavior, are comprehensively summarized and compared with other rod-like nanoparticles, for example, carbon nanotubes and fd virus. The consequences of the sensitive balance between liquid crystal formation and glass/gel formation are discussed in detail, in particular regarding the development toward control of helix pitch and orientation. Important topics for future studies are identified and suggestions for novel applications are made.

The important roles of reactive oxygen species in diseases related to aging and the necessity and benefits of antioxidative nutraceuticals in the prevention of diseases and promotion of healthy aging have been extensively reported in recent years. Oxygen is an essential component of living organisms. The generation of reactive oxygen species such as superoxide anion, hydrogen peroxide, hydroxyl radicals, and singlet oxygen is inevitable in aerobic metabolism of the body. Reactive oxygen species cause lipid oxidation, protein oxidation, DNA strand break and base modification, and modulation of gene expression. In the past several years, unprecedented progress has been made in the recognition and understanding of roles of reactive oxygen species in many diseases. These include atherosclerosis, vasospasms, cancers, trauma, stroke, asthma, hyperoxia, arthritis, heart attack, age pigments, dermatitis, cataractogenesis, retinal damage, hepatitis, liver injury, and periodontis, which are age-related. The body protects itself from the potential damages of reactive oxygen species. Its first line of defense is superoxide dismutases, glutathione peroxidases, and catalase. Scientists have indicated that antioxidant nutraceuticals supplied from daily diets quench the reactive oxygen species or are required as cofactors for antioxidant enzymes. Nutraceuticals play significant roles in the prevention of a number of age-related diseases and are essential for healthy aging. Epidemiological studies also reported the relevance of antioxidative nutraceuticals to health issues and the prevention of age-related diseases. Health-conscious consumers have made antioxidative nutraceuticals the leading trend in the food industry worldwide in recent years.

BACKGROUND: The worldwide demand for the organ replacement or tissue regeneration is increasing steadily. The advancements in tissue engineering and regenerative medicine have made it possible to regenerate such damaged organs or tissues into functional organ or tissue with the help of 3D bioprinting. The main component of the 3D bioprinting is the bioink, which is crucial for the development of functional organs or tissue structures. The bioinks used in 3D printing technology require so many properties which are vital and need to be considered during the selection. Combination of different methods and enhancements in properties are required to develop more successful bioinks for the 3D printing of organs or tissue structures. MAIN BODY: This review consists of the recent state-of-art of polymer-based bioinks used in 3D printing for applications in tissue engineering and regenerative medicine. The subsection projects the basic requirements for the selection of successful bioinks for 3D printing and developing 3D tissues or organ structures using combinations of bioinks such as cells, biomedical polymers and biosignals. Different bioink materials and their properties related to the biocompatibility, printability, mechanical properties, which are recently reported for 3D printing are discussed in detail. CONCLUSION: Many bioinks formulations have been reported from cell-biomaterials based bioinks to cell-based bioinks such as cell aggregates and tissue spheroids for tissue engineering and regenerative medicine applications. Interestingly, more tunable bioinks, which are biocompatible for live cells, printable and mechanically stable after printing are emerging with the help of functional polymeric biomaterials, their modifications and blending of cells and hydrogels. These approaches show the immense potential of these bioinks to produce more complex tissue/organ structures using 3D bioprinting in the future.

In this review article, we focus on the various types of materials used in biomedical implantable devices, including the polymeric materials used as substrates and for the packaging of such devices. Polymeric materials are used because of the ease of fabrication, flexibility, and their biocompatible nature as well as their wide range of mechanical, electrical, chemical, and thermal behaviors when combined with different materials as composites. Biocompatible and biostable polymers are extensively used to package implanted devices, with the main criteria that include gas permeability and water permeability of the packaging polymer to protect the electronic circuit of the device from moisture and ions inside the human body. Polymeric materials must also have considerable tensile strength and should be able to contain the device over the envisioned lifetime of the implant. For substrates, structural properties and, at times, electrical properties would be of greater concern. Section 1 gives an introduction of some medical devices and implants along with the material requirements and properties needed. Different synthetic polymeric materials such as polyvinylidene fluoride, polyethylene, polypropylene, polydimethylsiloxane, parylene, polyamide, polytetrafluoroethylene, poly(methyl methacrylate), polyimide, and polyurethane have been examined, and liquid crystalline polymers and nanocomposites have been evaluated as biomaterials that are suitable for biomedical packaging (section 2). A summary and glimpse of the future trend in this area has also been given (section 3). Materials and information used in this manuscript are adapted from papers published between 2010 and 2015 representing the most updated information available on each material.

Graphene-substrate-promoted human neural stem cell adhesion and its differentiation into neurons is reported. Microarray studies were performed to explore plausible explanation for this effect. Further, an electrical stimulation on differentiated cells via graphene electrodes is demonstrated. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors' routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner-instructor interaction (inter alia, communication, support, and presence) has a profound impact on students' satisfaction and learning outcomes. Thus, identifying how students and instructors perceive the impact of AI systems on their interaction is important to identify any gaps, challenges, or barriers preventing AI systems from achieving their intended potential and risking the safety of these interactions. To address this need for forward-looking decisions, we used Speed Dating with storyboards to analyze the authentic voices of 12 students and 11 instructors on diverse use cases of possible AI systems in online learning. Findings show that participants envision adopting AI systems in online learning can enable personalized learner-instructor interaction at scale but at the risk of violating social boundaries. Although AI systems have been positively recognized for improving the quantity and quality of communication, for providing just-in-time, personalized support for large-scale settings, and for improving the feeling of connection, there were concerns about responsibility, agency, and surveillance issues. These findings have implications for the design of AI systems to ensure explainability, human-in-the-loop, and careful data collection and presentation. Overall, contributions of this study include the design of AI system storyboards which are technically feasible and positively support learner-instructor interaction, capturing students' and instructors' concerns of AI systems through Speed Dating, and suggesting practical implications for maximizing the positive impact of AI systems while minimizing the negative ones.

Obesity is a prevalent and complex disease. The prevalence of obesity in Korea increased from 29.7% in 2010 to 35.7% in 2018, with the prevalence of abdominal obesity being 23.8% in 2018. Obesity contributes to medical costs and socioeconomic burden due to associated comorbidities. The treatment and management of obesity is changing based on new clinical evidence. The 2020 Korean Society for the Study of Obesity Guideline for the Management of Obesity in Korea summarizes evidence-based recommendations and treatment guidelines.

The recent expansion of the Internet of Things (IoT) and the consequent explosion in the volume of data produced by smart devices have led to the outsourcing of data to designated data centers. However, to manage these huge data stores, centralized data centers, such as cloud storage cannot afford auspicious way. There are many challenges that must be addressed in the traditional network architecture due to the rapid growth in the diversity and number of devices connected to the internet, which is not designed to provide high availability, real-time data delivery, scalability, security, resilience, and low latency. To address these issues, this paper proposes a novel blockchain-based distributed cloud architecture with a software defined networking (SDN) enable controller fog nodes at the edge of the network to meet the required design principles. The proposed model is a distributed cloud architecture based on blockchain technology, which provides low-cost, secure, and on-demand access to the most competitive computing infrastructures in an IoT network. By creating a distributed cloud infrastructure, the proposed model enables cost-effective high-performance computing. Furthermore, to bring computing resources to the edge of the IoT network and allow low latency access to large amounts of data in a secure manner, we provide a secure distributed fog node architecture that uses SDN and blockchain techniques. Fog nodes are distributed fog computing entities that allow the deployment of fog services, and are formed by multiple computing resources at the edge of the IoT network. We evaluated the performance of our proposed architecture and compared it with the existing models using various performance measures. The results of our evaluation show that performance is improved by reducing the induced delay, reducing the response time, increasing throughput, and the ability to detect real-time attacks in the IoT network with low performance overheads.

In this journal, Rainey and Steinbauer proposed a theory of effective government organizations, and Brewer and Selden conducted an empirical study with data from the 1996 Merit Principles Survey that confirmed most hypothesized relationships in the theoretical model of organizational performance. Following these studies, this study focuses only on the individual-level factors, such as job satisfaction, affective commitment, public service motivation, and organizational citizenship behavior. It empirically tests the effects of these variables on organizational performance in the public sector of Korea. When the survey data of 1,739 public employees in government agencies were analyzed, the hypothesized relationships in the proposed model were confirmed. I discuss the survey results in light of previous studies, especially those of Brewer and Selden.

Flexible tactile sensors capable of measuring mechanical stimuli via physical contact have attracted significant attention in the field of human-interactive systems. The utilization of tactile information can complement vision and/or sound interaction and provide new functionalities. Recent advancements in micro/nanotechnology, material science, and information technology have resulted in the development of high-performance tactile sensors that reach and even surpass the tactile sensing ability of human skin. Here, important advances in flexible tactile sensors over recent years are summarized, from sensor designs to system-level applications. This review focuses on the representative strategies based on design and material configurations for improving key performance parameters including sensitivity, detection range/linearity, response time/hysteresis, spatial resolution/crosstalk, multidirectional force detection, and insensitivity to other stimuli. System-level integration for practical applications beyond conceptual prototypes and promising applications, such as artificial electronic skin for robotics and prosthetics, wearable controllers for electronics, and bidirectional communication tools, are also discussed. Finally, perspectives on issues regarding further advances are provided.

Morphology-controlled nano- and microcrystals of ZnO (see figure) with different ratios of polar to nonpolar faces were synthesized through a soft-solution process. With these crystals, it is clearly demonstrated that a ZnO nanoplate with a large population of polar Zn(0001) faces is the most photocatalytically active morphology, underscoring the importance of the fine-tuning of face orientation in optimizing the activity of photocatalysts. Supporting information for this article is available on the WWW under http://www.wiley-vch.de/contents/jc_2089/2006/c1455_s.pdf or from the author. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

This paper proposes a novel tracker which is controlled by sequentially pursuing actions learned by deep reinforcement learning. In contrast to the existing trackers using deep networks, the proposed tracker is designed to achieve a light computation as well as satisfactory tracking accuracy in both location and scale. The deep network to control actions is pre-trained using various training sequences and fine-tuned during tracking for online adaptation to target and background changes. The pre-training is done by utilizing deep reinforcement learning as well as supervised learning. The use of reinforcement learning enables even partially labeled data to be successfully utilized for semi-supervised learning. Through evaluation of the OTB dataset, the proposed tracker is validated to achieve a competitive performance that is three times faster than state-of-the-art, deep network-based trackers. The fast version of the proposed method, which operates in real-time on GPU, outperforms the state-of-the-art real-time trackers.

The growth in international research on public service motivation (PSM) raises a number of important questions about the degree to which the theory and research developed in one country can contribute to our understanding of PSM in other counties. To help address this issue, this study revisits the conceptual and operational definitions of PSM to address weaknesses previously noted in the literature. Although some important steps have been taken to both improve and internationalize the PSM scale, this work has been done incrementally. In contrast, this study takes a more systematic and comprehensive approach by combining the efforts of international PSM scholars to develop and then test a revised measurement instrument for PSM in 12 countries. Although the resulting four dimensional 16-item measure of PSM reported here provides a better theoretical and empirical foundation for the measurement of PSM, our results suggest that the exact meaning and scaling of PSM dimensions are likely to differ across cultures and languages. These results raise serious concerns regarding the ability to develop a single universal scale of PSM, or making direct comparisons of PSM across countries.

This paper presents a new sensorless control scheme of a surface-mounted permanent-magnet (SMPM) motor using high-frequency voltage signal injection method based on the high-frequency impedance difference. In the SMPM motor, due to the flux of the permanent magnet, the stator core around the q-axis winding is saturated. This makes the magnetic saliency in the motor. This magnetic saliency has the information about the rotor position. The high-frequency voltage signal is injected into the motor in order to detect the magnetic saliency and estimate the rotor position. In this paper, the relationship between the high-frequency voltages and high-frequency currents is developed using the voltage equations at the high frequency, and the high-frequency impedance characteristics are analyzed experimentally under various conditions. The proposed sensorless control scheme makes it possible to drive the SMPM motor in the low-speed region including zero speed, even under heavy load conditions. The experimental results verify the performance of the proposed sensorless algorithm.

BACKGROUND AND AIMS: Smartphone addiction is a recent concern that has resulted from the dramatic increase in worldwide smartphone use. This study assessed the risk and protective factors associated with smartphone addiction in college students and compared these factors to those linked to Internet addiction. METHODS: College students (N = 448) in South Korea completed the Smartphone Addiction Scale, the Young's Internet Addiction Test, the Alcohol Use Disorders Identification Test, the Beck Depression Inventory I, the State-Trait Anxiety Inventory (Trait Version), the Character Strengths Test, and the Connor-Davidson Resilience Scale. The data were analyzed using multiple linear regression analyses. RESULTS: The risk factors for smartphone addiction were female gender, Internet use, alcohol use, and anxiety, while the protective factors were depression and temperance. In contrast, the risk factors for Internet addiction were male gender, smartphone use, anxiety, and wisdom/knowledge, while the protective factor was courage. Discussion These differences may result from unique features of smartphones, such as high availability and primary use as a tool for interpersonal relationships. CONCLUSIONS: Our findings will aid clinicians in distinguishing between predictive factors for smartphone and Internet addiction and can consequently be utilized in the prevention and treatment of smartphone addiction.

Soft wearable robots are good alternatives to rigid-frame exoskeletons because they are compact and lightweight. This article describes a soft wearable hand robot called the Exo-Glove that uses a soft tendon routing system and an underactuation adaptive mechanism. The proposed system can be used to develop other types of soft wearable robots. The glove part of the system is compact and weighs 194 g. The results conducted using a healthy subject showed sufficient performance for the execution of daily life activities, namely a pinch force of 20 N, a wrap grasp force of 40 N, and a maximum grasped object size of 76 mm. The use of an underactuation mechanism enabled the grasping of objects of various shapes without active control. A subject suffering from paralysis of the hands due to a spinal cord injury was able to use the glove to grasp objects of various shapes.

We propose novel cooperative spectrum sensing (CSS) algorithms for cognitive radio (CR) networks based on machine learning techniques which are used for pattern classification. In this regard, unsupervised (e.g., K-means clustering and Gaussian mixture model (GMM)) and supervised (e.g., support vector machine (SVM) and weighted K-nearest-neighbor (KNN)) learning-based classification techniques are implemented for CSS. For a radio channel, the vector of the energy levels estimated at CR devices is treated as a feature vector and fed into a classifier to decide whether the channel is available or not. The classifier categorizes each feature vector into either of the two classes, namely, the "channel available class" and the "channel unavailable class". Prior to the online classification, the classifier needs to go through a training phase. For classification, the K-means clustering algorithm partitions the training feature vectors into K clusters, where each cluster corresponds to a combined state of primary users (PUs) and then the classifier determines the class the test energy vector belongs to. The GMM obtains a mixture of Gaussian density functions that well describes the training feature vectors. In the case of the SVM, the support vectors (i.e., a subset of training vectors which fully specify the decision function) are obtained by maximizing the margin between the separating hyperplane and the training feature vectors. Furthermore, the weighted KNN classification technique is proposed for CSS for which the weight of each feature vector is calculated by evaluating the area under the receiver operating characteristic (ROC) curve of that feature vector. The performance of each classification technique is quantified in terms of the average training time, the sample classification delay, and the ROC curve. Our comparative results clearly reveal that the proposed algorithms outperform the existing state-of-the-art CSS techniques.