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Universal research index: An inclusive metric to quantify scientific research output

Journal of Academic Librarianship 2023年第3期49卷

作者： Keshavarz-Fathi, Mahsa Yazdanpanah, Niloufar Kolahchi, Sajad Ziaei, Heliya Darmstadt, Gary L. Dorigo, Tommaso Dochy, Filip Levin, Lisa Thongboonkerd, Visith Ogino, Shuji Chen, Wei-Hsin Perc, Matjaz Tremblay, Mark S. Olusanya, Bolajoko O. Rao, Idupulapati M. Hatziargyriou, Nikos Moradi-Lakeh, Maziar Bella, Federico Rosivall, Laszlo Gandomi, Amir H. Sorooshian, Armin Gupta, Manoj Gal, Ciprian Lozano, Andres M. Weaver, Connie Tanzer, Michael Poggi, Alessandro Sepanlou, Sadaf G. Weiskirchen, Ralf Jambrak, Anet Režek Torres, Pedro J. Capanoglu, Esra Barba, Francisco J. Ernest, Chua Kian Jon Sigman, Mariano Pluchino, Stefano Gharehpetian, Gevork B. Fereshtehnejad, Seyed-Mohammad Yang, Muh-Hwa Thomas, Sabu Cai, Wenju Comini, Elisabetta Scolding, Neil J. Myles, Paul S. Nieto, Juan J. Perry, George Sedikides, Constantine Rezaei, Nima School of Medicine Tehran University of Medical Sciences Tehran Iran Universal Scientific Education and Research Network (USERN) Iran Department of Pediatrics Stanford University School of Medicine Stanford CA United States Istituto Nazionale di Fisica Nucleare (INFN) Via Francesco Marzolo Sezione di Padova Italy High Impact Learning Academy Learning and Development Department Brussels Belgium Center for Marine Biodiversity and Conservation Integrative Oceanography Division Scripps Institution of Oceanography University of California San Diego San Diego CA United States Medical Proteomics Unit Office for Research and Development Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA United States Program in MPE Molecular Pathological Epidemiology Department of Pathology Brigham and Women's Hospital and Harvard Medical School Boston MA United States Broad Institute of MIT and Harvard Cambridge MA United States Department of Aeronautics and Astronautics National Cheng Kung University Tainan Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung 407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung 411 Taiwan Faculty of Natural Sciences and Mathematics University of Maribor Maribor Slovenia Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Complexity Science Hub Vienna Vienna Austria Alma Mater Europaea Maribor Slovenia Children's Hospital of Eastern Ontario Research Institute Department of Pediatrics University of Ottawa Ottawa ON Canada Centre for Healthy Start Initiative Ikoyi Lagos Nigeria Alliance of Bioversity International International Center for Tropical Agriculture Cali Colombia International Centre of Insect Physiology and Ecology (ICIPE) Nairobi Kenya School of Electrical and Computer Engineering Natio

Scientometrics and bibliometrics, the subfields of library and information science, deal with the quantity and quality of research outputs. Currently, various scientometric indices are being used to quantify and compare research outputs. The most widely known is the h-index. However, this index and its derivatives suffer from dependence on the mere count of a scholar's highly cited publications. To remedy this deficiency, we developed a novel index, the Universal Research Index (UR-Index) (https://***/UR-Index/) by which every single publication has its own impact on the total score. We developed this index by surveying international top 1 % cited scientists in various disciplines and included additional component variables such as publication type, leading role of a scholar, co-author count, and source metrics to this scientometric index. We acknowledge that unconscious biases built into the component variables included in the UR-Index might put research from specific groups at a disadvantage, thus continued efforts to improve equitable scholarly impact in science and academia are encouraged. © 2023 Elsevier Inc.

关键词： Citations CiteScore h-index Impact factor Leading author Research impact Scholarly impact Scholarly output Scientometrics UR-Index USERN

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The pathogenicity of COVID-19 and the role of pentraxin-3: An updated review study

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Pathology - Research and Practice 2022年 238卷

作者： Ria Margiana Satish Kumar Sharma Bilal Irshad Khan Ameer A. Alameri Maria Jade Catalan Opulencia Ali Thaeer Hammid Thulfeqar Ahmed Hamza Sharaf Khamrakulovich Babakulov Walid Kamal Abdelbasset Zanko Hassan Jawhar Department of Anatomy Faculty of Medicine Universitas Indonesia Jakarta Indonesia Master's Programme Biomedical Sciences Faculty of Medicine Universitas Indonesia Jakarta Indonesia Andrology Program Faculty of Medicine Universitas Airlangga Surabaya Indonesia Dr. Soetomo General Academic Hospital Surabaya Indonesia Department of Pharmacology Glocal School of Pharmacy The Glocal University Saharanpur India Mbbs Rawalpindi Medical University Rawalpindi Pakistan Department of Chemistry University of Babylon Iraq College of Business Administration Ajman University Ajman United Arab Emirates Computer Engineering Techniques Department Faculty of Information Technology Imam Ja’afar Al-Sadiq University Baghdad Iraq Medical laboratory techniques department Al-Mustaqbal University College Babylon Iraq Tashkent State Dental Institute Makhtumkuli Street 103 Tashkent 100047 Uzbekistan Research scholar Department of Scientific affairs Samarkand State Medical Institute Amir Temur Street 18 Samarkand Uzbekistan Department of Health and Rehabilitation Sciences College of Applied Medical Sciences Prince Sattam bin Abdulaziz University Al Kharj Saudi Arabia Department of Physical Therapy Kasr Al-Aini Hospital Cairo University Giza Egypt Department of Medical Laboratory Science College of Health Science Lebanese French University Kurdistan Region Iraq

In recent years, the COVID-19 pandemic has become one of the most crucial scientific issues in the world, and efforts to eradicate the disease are still ongoing. The acute inflammatory reaction associated with this disease is associated with several complications such as cytokine storm, multiple organ damage, lung fibrosis, and blood clots. PTX3, as part of the humoral innate immune systems, is one of the acute-phase proteins that perform various functions, such as modulating inflammation, repairing tissue, and recruiting immune cells. PTX3 is increased in people with SARS-CoV-2, and its level decreases with proper treatment. Therefore, it can be regarded as a suitable marker for the prognosis of the COVID-19 and evaluating the effectiveness of the treatment method applied. However, some studies have shown that PTX3 can be a double-edged sword and develop tumors by providing an immunosuppressive environment.

关键词： COVID-19 SARS-CoV-2 Pentraxin-3 Acute-phase proteins

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Implementation of Apriori Algorithm for Analysis of Consumer Purchase Patterns

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Journal of Physics: Conference Series 2019年第1期1255卷

作者： Suprianto Panjaitan Sulindawaty Muhammad Amin Sri Lindawati Ronal Watrianthos Hengki Tamando Sihotang Bosker Sinaga Teknik Informatika STMIK Pelita Nusantara Medan Sumatera Utara Indonesia Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan-Indonesia Program Doctoral Vocational Technology Education Postgraduate Engineering Faculty Padang State University Padang West Sumatera-Indonesia Manajemen Informatika AMIK Logika Sumatera Utara Indonesia Manajemen Informatika AMIK Labuhan Batu Sumatera Utara indonesia

Consumer purchasing patterns are a form of purchases made by consumers, whether someone or a lot of people to get the desired item by making a purchase transaction. One characteristic of the purchase pattern is the existence of acquiring something through exchanging money. This study aims to create an application that is used in determining consumer purchasing patterns by applying a priori algorithms and using Visual Basic 2010 as a tool for determining consumer purchase patterns. This application uses a priori algorithm calculation method where the sample consumer purchase data will be sorted and calculated by providing the value of the minium support and configuration parameters and based on the results of confidence the largest number of conclusions such as: can be used as information for determining sales, the application of a priori algorithms can provide information pattern combination item set from consumer purchase data that is with support above 15% and confidence above 50% on item set.

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Analysis backpropagation methods with neural network for prediction of children's ability in psychomotoric

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Journal of Physics: Conference Series 2018年第1期978卷 012085-012085页

作者： Izhari, F Dhany, H W Zarlis, M Sutarman Informatics Engineering Study Program Master Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

A good age in optimizing aspects of development is at the age of 4-6 years, namely with psychomotor development. Psychomotor is broader, more difficult to monitor but has a meaningful value for the child's life because it directly affects his behavior and deeds. Therefore, there is a problem to predict the child's ability level based on psychomotor. This analysis uses backpropagation method analysis with artificial neural network to predict the ability of the child on the psychomotor aspect by generating predictions of the child's ability on psychomotor and testing there is a mean squared error (MSE) value at the end of the training of 0.001. There are 30% of children aged 4-6 years have a good level of psychomotor ability, excellent, less good, and good enough.

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Elastic restricted Boltzmann machines for cancer data analysis

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Frontiers of Electrical and Electronic Engineering in China 2017年第2期5卷 159-172页

作者： Sai Zhang Muxuan Liang Zhongjun Zhou Chen Zhang Ning Chen Ting Chen Jianyang Zeng Institute for Interdisciplinary Information Sciences Tsinghua University Beijing 100084 China Department of Statistics University of Wisconsin-Madison Madison WI 53706-1685 USA Bioinformatics Division TNLIST Department of Computer Science and Technology Tsinghua University Beijing 100084 China Program in Computational Biology and Bioinformatics Univesity of Southern California Los Angeles CA 90089 USA

Background： Restricted Boltzmann machines （RBMs） are endowed with the universal power of modeling （binary） joint distributions. Meanwhile, as a result of their confining network structure, training RBMs confronts less difficulties when dealing with approximation and inference issues. But little work has been developed to fully exploit the capacity of these models to analyze cancer data, e.g., cancer genomic, transcriptomic, proteomic and epigenomic data. On the other hand, in the cancer data analysis task, the number of features/predictors is usually much larger than the sample size, which is known as the ＇~ 〉〉 N＂ problem and is also ubiquitous in other bioinformatics and computational biology fields. The ＂p 〉〉 N＂ problem puts the bias-variance trade-off in a more crucial place when designing statistical learning methods. However, to date, few RBM models have been particularly designed to address this issue. Methods： We propose a novel RBMs model, called elastic restricted Boltzmann machines （eRBMs）, which incorporates the elastic regularization term into the likelihood function, to balance the model complexity and sensitivity. Facilitated by the classic contrastive divergence （CD） algorithm, we develop the elastic contrastive divergence （eCD） algorithm which can train eRBMs efficiently. Results： We obtain several theoretical results on the rationality and properties of our model. We further evaluate the power of our model based on a challenging task -- predicting dichotomized survival time using the molecular profiling of tumors. The test results show that the prediction performance of eRBMs is much superior to that of the state-of-the-art methods. Conclusions： The proposed eRBMs are capable of dealing with the ＂p 〉〉 N＂ problems and have superior modeling performance over traditional methods. Our novel model is a promising method for future cancer data analysis.

关键词： RBMs regularization cancer data analysis survival time prediction

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FinnGen provides genetic insights from a well-phenotyped isolated population (vol 613, pg 508, 2023)

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NATURE 2023年第7952期615卷 E19-E19页

作者： Kurki, Mitja I. Karjalainen, Juha Palta, Priit Sipila, Timo P. Kristiansson, Kati Donner, Kati M. Reeve, Mary P. Laivuori, Hannele Aavikko, Mervi Kaunisto, Mari A. Loukola, Anu Lahtela, Elisa Mattsson, Hannele Laiho, Paivi Parolo, Pietro Della Briotta Lehisto, Arto A. Kanai, Masahiro Mars, Nina Ramo, Joel Kiiskinen, Tuomo Heyne, Henrike O. Veerapen, Kumar Rueger, Sina Lemmela, Susanna Zhou, Wei Ruotsalainen, Sanni Parn, Kalle Hiekkalinna, Tero Koskelainen, Sami Paajanen, Teemu Llorens, Vincent Gracia-Tabuenca, Javier Siirtola, Harri Reis, Kadri Elnahas, Abdelrahman G. Sun, Benjamin Foley, Christopher N. Aalto-Setala, Katriina Alasoo, Kaur Arvas, Mikko Auro, Kirsi Biswas, Shameek Bizaki-Vallaskangas, Argyro Carpen, Olli Chen, Chia-Yen Dada, Oluwaseun A. Ding, Zhihao Ehm, Margaret G. Eklund, Kari Farkkila, Martti Finucane, Hilary Ganna, Andrea Ghazal, Awaisa Graham, Robert R. Green, Eric M. Hakanen, Antti Hautalahti, Marco Hedman, Asa K. Hiltunen, Mikko Hinttala, Reetta Hovatta, Iiris Hu, Xinli Huertas-Vazquez, Adriana Huilaja, Laura Hunkapiller, Julie Jacob, Howard Jensen, Jan-Nygaard Joensuu, Heikki John, Sally Julkunen, Valtteri Jung, Marc Junttila, Juhani Kaarniranta, Kai Kahonen, Mika Kajanne, Risto Kallio, Lila Kalviainen, Reetta Kaprio, Jaakko Kerimov, Nurlan Kettunen, Johannes Kilpelainen, Elina Kilpi, Terhi Klinger, Katherine Kosma, Veli-Matti Kuopio, Teijo Kurra, Venla Laisk, Triin Laukkanen, Jari Lawless, Nathan Liu, Aoxing Longerich, Simonne Magi, Reedik Makela, Johanna Makitie, Antti Malarstig, Anders Mannermaa, Arto Maranville, Joseph Matakidou, Athena Meretoja, Tuomo Mozaffari, Sahar V. Niemi, Mari E. K. Niemi, Marianna Niiranen, Teemu O'Donnell, Christopher J. Obeidat, Ma'En Okafo, George Ollila, Hanna M. Palomaki, Antti Palotie, Tuula Partanen, Jukka Paul, Dirk S. Pelkonen, Margit Pendergrass, Rion K. Petrovski, Slave Pitkaranta, Anne Platt, Adam Pulford, David Punkka, Eero Pussinen, Pirkko Raghavan, Neha Rahimov, Fedik Rajpal, Deepak Renaud, Nicole A. Riley-Gillis, Bridget Rodosthenous, Rodostheni Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Estonian Genome Centre Institute of Genomics University of Tartu Tartu Estonia Medical and Clinical Genetics University of Helsinki and Helsinki University Hospital Helsinki Finland Department of Obstetrics and Gynecology Tampere University Hospital Tampere Finland Faculty of Medicine and Health Technology Center for Child Adolescent and Maternal Health University of Tampere Tampere Finland Department of Biomedical Informatics Harvard Medical School Boston MA USA Digital Health Center Hasso Plattner Institute for Digital Engineering University of Potsdam Potsdam Potsdam Germany Hasso Plattner Institute for Digital Health at Mount Sinai Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA Finnish Institute for Health and Welfare (THL) Helsinki Finland Department of Public Health University of Helsinki Helsinki Finland Anesthesia Critical Care and Pain Medicine Massachusetts General Hospital Boston MA USA Abdominal Center Endocrinology Helsinki University Hospital Helsinki Finland Folkhalsan Research Center Helsinki Finland Research Program of Clinical and Molecular Metabolism University of Helsinki Helsinki Finland Biocenter Oulu University of Oulu Oulu Finland Computational Medicine Center for Life Course Health Research Faculty of Medicine University of Oulu Oulu Finland Turku University Hospital and University of Turku Turku Finland University of Turku Turku Finland Helsinki Biobank University of Helsinki and Hospital District of Helsinki and Uusimaa Helsinki Finland TAUCHI Research Center

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Application of Message Security Application Using Vigenere Cipher Algorithm Utilizing One Time Pad (OTP) Algorithm as a Key Generator

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Journal of Physics: Conference Series 2019年第1期1363卷 012080-012080页

作者： Pardede, A M H Lorena Perbina Br Sitepu Zarlis, Muhammad Tulus Iskandar, Akbar Sriadhi, S Manurung, Rosida Tiurma Nurintan Asyiah Siregar Sari, Ayu Esteka Yunawati, Sri Mursyidah, M Mursalin, M Kurniasih, Nuning Kurniawan, Citra Winarno, Edy STMIK Kaputama Binjai Sumatera Utara Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Program Study of Accounting Pasir Pengaraian University Riau Indonesia Departement of Information Technology and Computer Politeknik Negeri Lhokseumawe Aceh Indonesia Department of Mathematics Education Universitas Malikussaleh Aceh Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Cryptography is the science and art of maintaining the security of messages when messages are sent from one place to another. One of the ways securing the form of text message information is by the encryption process using the Vigenere Cipher algorithm and utilizing the One Time Pad (OTP) algorithm as a key generator, where the message will be random when it is opened. The message encryption process used the vigenere cipher algorithm while OTP is used to secure the key with the same formula. After this research has been done, an application was designed to secure text messages by converting the text message into a random message so that the message was unreadable due to a secret message that could not be known by others. The results achieved can secure an encrypted message that cannot be reopened and if those messages were reopened, they must be decrypted.

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Author Correction: Pathway and network analysis of more than 2500 whole cancer genomes

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Nature communications 2022年第1期13卷 7566页

作者： Matthew A Reyna David Haan Marta Paczkowska Lieven P C Verbeke Miguel Vazquez Abdullah Kahraman Sergio Pulido-Tamayo Jonathan Barenboim Lina Wadi Priyanka Dhingra Raunak Shrestha Gad Getz Michael S Lawrence Jakob Skou Pedersen Mark A Rubin David A Wheeler Søren Brunak Jose M G Izarzugaza Ekta Khurana Kathleen Marchal Christian von Mering S Cenk Sahinalp Alfonso Valencia Jüri Reimand Joshua M Stuart Benjamin J Raphael Department of Computer Science Princeton University Princeton NJ 08540 USA. Department of Biomedical Informatics Emory University Atlanta GA 30322 USA. Department of Biomolecular Engineering and UC Santa Cruz Genomics Institute University of California Santa Cruz Santa Cruz CA 95060 USA. Computational Biology Program Ontario Institute for Cancer Research Toronto Ontario Canada. Department of Information Technology IDLab Ghent University IMEC Ghent the Netherlands. Department of Plant Biotechnology and Bioinformatics Ghent University Ghent the Netherlands. Barcelona Supercomputing Center (BSC) Barcelona 08034 Spain. Department of Clinical and Molecular Medicine Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway. Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics University of Zurich CH-8057 Zurich Switzerland. Department of Pathology and Molecular Pathology University Hospital Zurich CH-8091 Zurich Switzerland. Department of Physiology and Biophysics Weill Cornell Medicine New York NY 10065 USA. Vancouver Prostate Centre 2660 Oak Street Vancouver BC V6H 3Z6 Canada. The Broad Institute of MIT and Harvard Cambridge MA 02124 USA. Massachusetts General Hospital Center for Cancer Research Charlestown MA 02129 USA. Harvard Medical School 250 Longwood Avenue Boston MA 02115 USA. Massachusetts General Hospital Department of Pathology Boston MA 02114 USA. Department of Molecular Medicine (MOMA) Aarhus University Hospital Aarhus Denmark. Bioinformatics Research Centre (BiRC) Aarhus University Aarhus Denmark. Human Genome Sequencing Center Baylor College of Medicine Houston TX 77030 USA. DTU Bioinformatics Department of Bio and Health Informatics Technical University of Denmark Kemitorvet 2800 Kongens Lyngby Denmark. Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen 2200 Copenhagen Denmark. De

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The hybrid algorithm for product design in multimedia

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International Journal of Applied Systemic Studies 2017年第1-3期7卷 78-91页

作者： Huang, Ching-Lien Chen, Yung-Hui Tseng, Chun-Hsiung Wan, Tian-Long Shen, Mars Department of Industrial Management Lunghwa University of Science and Technology No. 300 Sec. 1 Wanshou Rd. Guishan Taoyuan City33306 Taiwan Department of Computer Information and Network Engineering LungHwa University of Science and Technology No. 300 Sec. 1 Wanshou Rd. Guishan District Taoyuan City33306 Taiwan Department of Communications Engineering Yuan Ze University No. 135 Yuandong Rd. Zhongli Dist. Taoyuan City320 Taiwan Department of Information Management Lunghwa University of Science and Technology No. 300 Sec. 1 Wanshou Rd. Guishan Taoyuan City33306 Taiwan Department of Master’s Program of Business Administration Lunghwa University of Science and Technology No. 300 Sec. 1 Wanshou Rd. Guishan Taoyuan City33306 Taiwan

It is the key successful factors for the manufacture industry that create and select the key parameters in product design to match customer requirements in multimedia. Previous literature studies are focused on the development of customer requirements or parameter selection in product design but not the development of customer demand modelling and product parameter selections in multimedia. In this way we can achieve the purpose of meeting customer demand for product design in multimedia. Kano is a successful method to solve the customer requirements selections issues. And, the theory of inventive problem solving (TRIZ) method is a method to solve the contradiction of product design. Therefore;the integration of the Kano and theory of inventive problem solving (TRIZ) methods is proposed to solve the cable product design in multimedia. This algorithm is also verified in an electronic manufacture. In summary, the proposed algorithm can be helpful by creating a product system in multimedia in this study. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Product design

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Augmented Reality for Presenting Local Wisdom: Sumatera Utara Traditional House

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Journal of Physics: Conference Series 2019年第1期1235卷

作者： M F Syahputra R Aulia O S Sitompul U Andayani D Abdullah S Sriadhi R F Nanuru M D Utama R T Manurung H Djanggih E Mouw Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Faculty of Law Universitas Tompotika Luwuk Banggai Indonesia Faculty of Social and Human Sciences Universitas Halmahera Indonesia

Augmented Reality is a technology that allows users to see the real world, with virtual objects placed on it or combined with the real world. Augmented Reality itself can be applied to various things, including as an educational media. In the field of education, technology can be used a culture introduction to society. One part of Indonesian culture is traditional houses. Traditional house is a building that symbolizes the culture of the local community. In North Sumatra itself, there are several traditional houses that have different forms. The use of Vuforia SDK in the construction of this application can display augmented objects in the form of 3-dimentional objects and also provide information on the house. This application will run on the Android mobile platform to make it easier for users to access it. In addition, users can choose their own objects to be used as markers to make the application use much easier.

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