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[Applying the Concept of Grief Counseling in Caring for an Elderly Dialysis Patient With Bereavement Due to the Death of Spouse: A Nursing Care Experience]

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Hu li za zhi The journal of nursing 2018年第5期65卷 98-104页

作者： Pei-Yu Cheng Li Fang BSN RN Department of Nursing Pingtung Christian Hospital and Graduate Student Master of Science Program in Health Care Department of Nursing Meiho University Taiwan ROC. PhD RN Assistant Professor Department of Nursing Fooyin University Taiwan ROC. fangli72catholic36@***.

This article describes a 76-year-old dialysis patient who experienced widowhood. The nursing intervention occurred between April 2nd to June 28th, 2015. Using observation, interviews, medical records and health examinations, the authors assessed the patient's physical, psychological, social, intellectual, and spiritual status. The patient not only presented poor appetite, insomnia, hopelessness, and grief but had also attempted suicide. Thus, three health problems were identified, including dysfunctional grieving, hopelessness, and sleep pattern disturbance. Employing caring, active listening, and empathy, we helped the patient achieve the four tasks of Worden's Mourning: (1) to accept the reality of loss; (2) to work through the pain of grief; (3) to adjust to an environment in which the deceased is missing; and (4) to emotionally relocate the deceased and move on with life. With comprehensive and persistent nursing intervention, the patient got the support from her family members and eventually readapted to life without the deceased and continued to take hemodialysis and found new life motivation.

关键词： grief grief counseling hemodialysis widowhood

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Solving the conjugacy decision problem via machine learning

arXiv

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arXiv 2017年

作者： GRYAK, JONATHAN HARALICK, ROBERT M. KAHROBAEI, DELARAM CUNY Graduate Center PhD Program in Computer Science City University of New York CUNY Graduate Center PhD Program in Computer Science City University of New York CUNY Graduate Center PhD Program in Computer Science and NYCCT Mathematics Department City University of New York

Machine learning and pattern recognition techniques have been successfully applied to algorithmic problems in free groups. In this paper, we seek to extend these techniques to finitely presented non-free groups, with a particular emphasis on polycyclic and metabelian groups that are of interest to non-commutative cryptography. As a prototypical example, we utilize supervised learning methods to construct classifiers that can solve the conjugacy decision problem, i.e., determine whether or not a pair of elements from a specified group are conjugate. The accuracies of classifiers created using decision trees, random forests, and N-tuple neural network models are evaluated for several non-free groups. The very high accuracy of these classifiers suggests an underlying mathematical relationship with respect to conjugacy in the tested groups.20F10, 68T05 Copyright © 2017, The Authors. All rights reserved.

关键词： Decision trees

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Identification of gene expression signatures for psoriasis classification using machine learning techniques

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Medicine in Omics 2021年 1卷

作者： Nguyen Quoc Khanh Le Duyen Thi Do Trinh-Trung-Duong Nguyen Ngan Thi Kim Nguyen Truong Nguyen Khanh Hung Nguyen Thi Thu Trang Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei City 106 Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei City 106 Taiwan Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City 106 Taiwan Department of Computer Science and Engineering Yuan Ze University Chung-Li 32003 Taiwan School of Nutrition and Health Sciences Taipei Medical University Taipei City 110 Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan Orthopedic and Trauma Department Cho Ray Hospital Ho Chi Minh City Viet Nam International PhD Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan

Psoriasis classification requires the accurate identification of the lesional types for the early and effective diagnosis and it is worth interesting that the normal and psoriasis cell tissues exhibit different gene expression. Therefore, gene expression data is an effective source for psoriasis classification and there is a challenge regarding the selection of suitable gene signatures for its purpose. In this present study, the gene expression-based microarray data were used and 35 expression features linked with psoriasis were utilized to feed into our machine learning model. Overall, the performance of our model based on 35 mentioned-above features surpassed that of other state-of-the-art classifiers with an average accuracy of 98.3%, recall of 98.6%, and precision of 98% in 5-fold cross-validation tests. We also validate our model on two different sets of psoriasis and the performance results are significant. These results have suggested that our 35 expression signatures have been identified as key features for classifying samples between lesion and non-lesion. More specifically, the expression levels of few genes i.e., FABP5 , TGM1 , or BCAR3 are discovered as newly potential biomarkers for psoriasis classification and treatment with high confidence. This study, therefore, could shed light on developing the prediction models for psoriasis classification and treatment using gene expression profiles.

关键词： Psoriasis classification Random forest Gene expression Feature selection Machine learning FABP5 Dermatology

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Practical and secure outsourcing of discrete log group exponentiation to a single malicious server 8

Practical and secure outsourcing of discrete log group expon...

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8th ACM Cloud Computing Security Workshop, CCSW 2017

作者： Crescenzo, Giovanni Di Khodjaeva, Matluba Kahrobaei, Delaram Shpilrain, Vladimir Vencore Labs Basking RidgeNJ07920 United States CUNY Graduate Center New YorkNY10016 United States PhD Program in Computer Science CUNY Graduate Center New YorkNY10016 United States

ISBN: (纸本)9781450353939

Group exponentiation is an important operation used in many public-key cryptosystems and, more generally, cryptographic protocols. To expand the applicability of these solutions to computationally weaker devices, it has been advocated that this operation is outsourced from a computationally weaker client to a computationally stronger server, possibly implemented in a cloud-based architecture. While preliminary solutions to this problem considered mostly honest servers, or multiple separated servers, some of which honest, solving this problem in the case of a single (logical), possibly malicious, server, has remained open since a formal cryptographic model was introduced in [20]. Several later attempts either failed to achieve privacy or only bounded by a constant the (security) probability that a cheating server convinces a client of an incorrect result. In this paper we solve this problem for a large class of cyclic groups, thus making our solutions applicable to many cryptosystems in the literature that are based on the hardness of the discrete logarithm problem or on related assumptions. Our main protocol satisfies natural correctness, security, privacy and efficiency requirements, where the security probability is exponentially small. In our main protocol, with very limited offline computation and server computation, the client can delegate an exponentiation to an exponent of the same length as a group element by performing an exponentiation to an exponent of short length (i.e., the length of a statistical parameter). We also show an extension protocol that further reduces client computation by a constant factor, while increasing offline computation and server computation by about the same factor.

关键词： Group theory

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Facilitating Interdisciplinary graduate Education: Barriers, Solutions, and Needed Innovations

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Change: The Magazine of Higher Learning 2018年第5期50卷 53-59页

作者： Meredith Welch-Devine Alana Shaw Julie Coffield Nik Heynen Meredith Welch-Devine is the Director of Interdisciplinary and Innovative Initiatives for the University of Georgia Graduate School. In addition to helping develop and administer interdisciplinary programs for the university she has a research interest in interdisciplinary team science and interdisciplinary training.http://***/0000-0001-8519-4585 Alana Shaw received her PhD from the University of Georgia in 2016 and is now the Environmental Coordinator for the Village of Wainwright. Shaw was a student in the interdisciplinary Integrative Conservation program. Julie Coffield recently returned to the faculty after serving as Associate Dean of the Graduate School. She also formerly directed the Interdisciplinary Toxicology Program at UGA. Nik Heynen is the immediate past director of the interdisciplinary Integrative Conservation program.

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关键词： INTERDISCIPLINARY education graduate education HUMAN resources departments studentS TRAINING

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The Biodiversity of Flora and Fauna in the Re-vegetation Area in The Post-Mining Area of Pongkor

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IOP Conference Series: Earth and Environmental science 2020年第1期501卷

作者： A Kusumoarto A Gunawan Machfud A Hikmat Doctoral Student Program Natural Resource and Environmental Management Science School of Post-Graduate IPB University Jl. Raya Pajajaran Bogor Indonesia 16143 Lecturer in Architecture Study Program Faculty of Technic and Computer Science Indraprasta PGRI University Jl. Raya Nangka No. 58C RT.5/RW.5 Tanjung Barat Kecamatan Jagakarsa Kota Jakarta Selatan Daerah Khusus Ibukota Jakarta 12530 Lecturer in Landscape Architecture Department IPB University Jl. Raya Darmaga Bogor Indonesia 16680 Lecturer in AgroIndustrial Technology Department IPB University Jl.Raya Darmaga Bogor Indonesia 16680 Lecturer in Conservation of Forest and Ecotourism Department IPB University Jl. Raya Darmaga Bogor Indonesia 16680

The Pongkor post-mining area is designated as one of the ecotourism areas in Bogor. This area has biodiversity of flora and fauna. This study aims to: (1) analysis the importance value index (IVI) of flora types; (2) analysis species richness index, species diversity index, and relative species abundance index; (3) analysis the beauty, the uniqueness and the rarity of the flora and fauna types. The method used in this research is quantitative descriptive. Based on the identification results, 185 species of flora are distributed in this region. During the rainy season, 15 species of herpetofauna were identified, 32 types of aves, and 4 types of mammals, while in the dry season 19 species of herpetofauna were identified, 23 types of aves, and 2 types of mammals. Based on the results of the analysis conducted on these flora and fauna, there are flora species that have high IVI values and some beautiful and unique flora species that are in the category of endangered species. Besides that, there are also fauna species which have a value of species richness index, species diversity index, and relative species abundance index, as well as some beautiful, unique, and fauna species that are in the category of endangered species.

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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Optimizing regional power production under thermal pollution constraints 7

Optimizing regional power production under thermal pollution...

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7th International Green and Sustainable Computing Conference, IGSC 2016

作者： Bald, Samuel Johnson, Matthew P. Rybalov, Levi PhD Program in Computer Science Graduate Center City University of New York United States Department of Mathematics and Computer Science Lehman College City University of New York United States

ISBN: (纸本)9781509051175

A majority of electricity generation in the US is produced by thermoelectric power plants which require a constant supply of water for cooling. Many of these plants eject large quantities of hot water that was used for cooling into an adjacent river - a phenomenon known as thermal pollution - causing harm to local ecosystems and aquatic life. Commonly, plants lie within interconnected river networks, whence thermal pollution from plants upstream is translated to plants dowstream, causing less-effective cooling, and decreases in efficiency. By default, plants are managed locally, and government regulations combating thermal pollution take the form of local river temperature constraints. We propose analyzing this situation regionally, seeking to balance the trade-off between power demand and required pollution minimization in a region. We first consider fractional variants of this problem where plants may operate at some fraction of their total capacity. We provide optimal poly-time algorithms for such cases. We show that the integer version of the problem - where plants are either fully on or off - is already NP-hard when the river network topology is a path graph. We provide a dynamic programming FPTAS in this case. We compare the results of our algorithms to baseline heuristics in simulation. © 2016 IEEE.

关键词： Cooling

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BHEL Smart Wall Blowing System: New Product Development in Manufacturing Industry

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Vikalpa 2021年第4期45卷 240 - 249页

作者： Abhishek Kumar R. Dhanuskodi R. Kaliappan K. Nandakumar Abhishek Kumar teaches design philosophies at Anant National University Ahmedabad. He earned his Ph.D in Management from Pondicherry University. He is an Economics graduate from Calcutta University and MBA from BIM Trichy. He has published more than 20 articles in reputed international journals has authored two books written articles and columns for newspapers and is quoted on issues related to leadership and marketing by various media platforms. His research work comprises construction of brand personality scale for media aesthetics and phenomenological design. His recent publications are on philosophy of a photograph hermeneutic reality of product and on philosophy of intimate spaces. R. Dhanuskodi has nearly 40 years of R&D experience at BHEL India in technical areas applicable for thermal power plants. He is a life member of The Institution of Engineers (India) and The Combustion Institute. He has won two BHEL’s Excel awards under the best author category for technical papers. He has visited France Netherlands and Germany under Indo-Europe Clean Coal Development Program. He has guided 42 UG PG and PhD project works. He holds 11 patents 40 copyrights and 2 design registrations. He has presented papers in 20 conferences and published in 10 national and international journals. R. Kaliappan completed his bachelors in electrical and electronics engineering and Masters in Computer Science. He has 36 years of research experience in different fields of power generation and power plant subsystems such as heat transfer studies on boiler circulation efficiency improvements of boiler subsystems product improvements/ enhancements and setting up test facilities for research studies. He has published a number of technical papers on MHD power generation and heat transfer studies in various national and international journals. He has more than 25 patents and copyrights on products development related to power boilers. He has won BHEL’S gold medal for product development for Smart Wall Blowing system. K. Nandakumar

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