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Journal articles on the topic 'Rare rules'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Pariñas, Miriam P. "Mining Association Rules for Frequent and Rare Items Using Relative Multiple Supports." Journal of Advanced Research in Dynamical and Control Systems 12, no. 01-Special Issue (February 13, 2020): 285–92. http://dx.doi.org/10.5373/jardcs/v12sp1/20201074.

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2

Hayden, Erika Check. "Licence rules hinder work on rare disease." Nature 470, no. 7334 (February 2011): 318–19. http://dx.doi.org/10.1038/470318a.

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3

Werdiningsih, Indah, Rimuljo Hendradi, Barry Nuqoba, and Elly Ana. "Identification of Risk Factors for Early Childhood Diseases Using Association Rules Algorithm with Feature Reduction." Cybernetics and Information Technologies 19, no. 3 (September 1, 2019): 154–67. http://dx.doi.org/10.2478/cait-2019-0031.

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Abstract This paper introduces a technique that can efficiently identify symptoms and risk factors for early childhood diseases by using feature reduction, which was developed based on Principal Component Analysis (PCA) method. Previous research using Apriori algorithm for association rule mining only managed to get the frequent item sets, so it could only find the frequent association rules. Other studies used ARIMA algorithm and succeeded in obtaining the rare item sets and the rare association rules. The approach proposed in this study was to obtain all the complete sets including the frequent item sets and rare item sets with feature reduction. A series of experiments with several parameter values were extrapolated to analyze and compare the computing performance and rules produced by Apriori algorithm, ARIMA, and the proposed approach. The experimental results show that the proposed approach could yield more complete rules and better computing performance.

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4

Wang, Dingsheng, Zhongying Wang, Peng Zhao, Wen Zheng, Qing Peng, Liqin Liu, Xueyuan Chen, and Yadong Li. "Rare-Earth Oxide Nanostructures: Rules of Rare-Earth Nitrate Thermolysis in Octadecylamine." Chemistry - An Asian Journal 5, no. 4 (April 1, 2010): 925–31. http://dx.doi.org/10.1002/asia.200900499.

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5

Sousa, Ricardo, and Fatima Rodrigues. "Mining association rules with rare and frequent items." International Journal of Knowledge Engineering and Data Mining 2, no. 4 (2013): 237. http://dx.doi.org/10.1504/ijkedm.2013.059290.

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6

Kai, Masaru, Arata Tanaka, and Takeo Jo. "Selection Rules in Resonant 4f Photoemission for Rare Earths." Journal of the Physical Society of Japan 64, no. 7 (July 15, 1995): 2356–59. http://dx.doi.org/10.1143/jpsj.64.2356.

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7

Thole, B. T., and G. van der Laan. "Sum rules for magnetic dichroism in rare earth 4fphotoemission." Physical Review Letters 70, no. 16 (April 19, 1993): 2499–502. http://dx.doi.org/10.1103/physrevlett.70.2499.

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8

Showstack, Randy. "Trade Group Rules Against China in Rare Earths Dispute." Eos, Transactions American Geophysical Union 95, no. 14 (April 8, 2014): 119. http://dx.doi.org/10.1002/2014eo140004.

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9

YIN Min, 尹民, 闻军 WEN Jun, and 段昌奎 DUAN Chang-kui. "Transition Selection Rules of Rare-earth in Optical Materials." Chinese Journal of Luminescence 32, no. 7 (2011): 643–49. http://dx.doi.org/10.3788/fgxb20113207.0643.

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10

Mustafa, M. D., N. F. Nabila, D. J. Evans, M. Y. Saman, and A. Mamat. "Association rules on significant rare data using second support." International Journal of Computer Mathematics 83, no. 1 (January 2006): 69–80. http://dx.doi.org/10.1080/00207160500113330.

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11

Görller-Walrand, C., and L. Fluyt-Adriaens. "Selection rules for rare earth magnetic circular dichroism spectra." Journal of the Less Common Metals 112, no. 1-2 (October 1985): 175–91. http://dx.doi.org/10.1016/0022-5088(85)90023-2.

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12

Villar, Sofía S. "BANDIT STRATEGIES EVALUATED IN THE CONTEXT OF CLINICAL TRIALS IN RARE LIFE-THREATENING DISEASES." Probability in the Engineering and Informational Sciences 32, no. 2 (June 7, 2017): 229–45. http://dx.doi.org/10.1017/s0269964817000146.

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In a rare life-threatening disease setting the number of patients in the trial is a high proportion of all patients with the condition (if not all of them). Further, this number is usually not enough to guarantee the required statistical power to detect a treatment effect of a meaningful size. In such a context, the idea of prioritizing patient benefit over hypothesis testing as the goal of the trial can lead to a trial design that produces useful information to guide treatment, even if it does not do so with the standard levels of statistical confidence. The idealized model to consider such an optimal design of a clinical trial is known as a classic multi-armed bandit problem with a finite patient horizon and a patient benefit objective function. Such a design maximizes patient benefit by balancing the learning and earning goals as data accumulates and given the patient horizon. On the other hand, optimally solving such a model has a very high computational cost (many times prohibitive) and more importantly, a cumbersome implementation, even for populations as small as a hundred patients. Several computationally feasible heuristic rules to address this problem have been proposed over the last 40 years in the literature. In this paper, we study a novel heuristic approach to solve it based on the reformulation of the problem as a Restless bandit problem and the derivation of its corresponding Whittle Index (WI) rule. Such rule was recently proposed in the context of a clinical trial in Villar, Bowden, and Wason [16]. We perform extensive computational studies to compare through both exact value calculations and simulated values the performance of this rule, other index rules and simpler heuristics previously proposed in the literature. Our results suggest that for the two and three-armed case and a patient horizon less or equal than a hundred patients, all index rules are a priori practically identical in terms of the expected proportion of success attained when all arms start with a uniform prior. However, we find that a posteriori, for specific values of the parameters of interest, the index policies outperform the simpler rules in every instance and specially so in the case of many arms and a larger, though still relatively small, total number of patients with the diseases. The very good performance of bandit rules in terms of patient benefit (i.e., expected number of successes and mean number of patients allocated to the best arm, if it exists) makes them very appealing in context of the challenge posed by drug development and treatment for rare life-threatening diseases.

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13

Borah, Anindita, and Bhabesh Nath. "An Efficient Method for Mining Rare Association Rules: A Case Study on Air Pollution." International Journal on Artificial Intelligence Tools 30, no. 04 (June 2021): 2150018. http://dx.doi.org/10.1142/s0218213021500184.

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Most pattern mining techniques almost singularly focus on identifying frequent patterns and very less attention has been paid to the generation of rare patterns. However, in several domains, recognizing less frequent but strongly related patterns have greater advantage over the former ones. Identification of compelling and meaningful rare associations among such patterns may proved to be significant for air quality management that has become an indispensable task in today’s world. The rare correlations between air pollutants and other parameters may aid in restricting the air pollution to a manageable level. To this end, efficient and competent rare pattern mining techniques are needed that can generate the complete set of rare patterns, further identifying significant rare association rules among them. Moreover, a notable issue with databases is their continuous update over time due to the addition of new records. The users requirement or behavior may change with the incremental update of databases that makes it difficult to determine a suitable support threshold for the extraction of interesting rare association rules. This paper, presents an efficient rare pattern mining technique to capture the complete set of rare patterns from a real environmental dataset. The proposed approach does not restart the entire mining process upon threshold update and generates the complete set of rare association rules in a single database scan. It can effectively perform incremental mining and also provides flexibility to the user to regulate the value of support threshold for generating the rare patterns. Significant rare association rules representing correlations between air pollutants and other environmental parameters are further extracted from the generated rare patterns to identify the substantial causes of air pollution. Performance analysis shows that the proposed method is more efficient than existing rare pattern mining approaches in providing significant directions to the domain experts for air pollution monitoring.

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14

Yun, Hyunyoon, Danshim Ha, Buhyun Hwang, and Keun Ho Ryu. "Mining association rules on significant rare data using relative support." Journal of Systems and Software 67, no. 3 (September 2003): 181–91. http://dx.doi.org/10.1016/s0164-1212(02)00128-0.

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15

van der Sanden, G. C. M., P. E. S. Wormer, A. van der Avoird, J. Schleipen, and J. J. ter Meulen. "On the propensity rules for inelastic NH3–rare gas collisions." Journal of Chemical Physics 103, no. 23 (December 15, 1995): 10001–4. http://dx.doi.org/10.1063/1.469903.

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16

Waldman, Marvin, and A. T. Hagler. "New combining rules for rare gas van der waals parameters." Journal of Computational Chemistry 14, no. 9 (September 1993): 1077–84. http://dx.doi.org/10.1002/jcc.540140909.

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17

Görller‐Walrand, C., M. Behets, P. Porcher, and I. Laursen. "Selection rules in rare earth MCD spectra. An experimental confirmation." Journal of Chemical Physics 83, no. 9 (November 1985): 4329–37. http://dx.doi.org/10.1063/1.449046.

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18

Nowak-Brzezińska, Agnieszka, and Czesław Horyń. "Exploration of Outliers in If-Then Rule-Based Knowledge Bases." Entropy 22, no. 10 (September 29, 2020): 1096. http://dx.doi.org/10.3390/e22101096.

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The article presents both methods of clustering and outlier detection in complex data, such as rule-based knowledge bases. What distinguishes this work from others is, first, the application of clustering algorithms to rules in domain knowledge bases, and secondly, the use of outlier detection algorithms to detect unusual rules in knowledge bases. The aim of the paper is the analysis of using four algorithms for outlier detection in rule-based knowledge bases: Local Outlier Factor (LOF), Connectivity-based Outlier Factor (COF), K-MEANS, and SMALLCLUSTERS. The subject of outlier mining is very important nowadays. Outliers in rules If-Then mean unusual rules, which are rare in comparing to others and should be explored by the domain expert as soon as possible. In the research, the authors use the outlier detection methods to find a given number of outliers in rules (1%, 5%, 10%), while in small groups, the number of outliers covers no more than 5% of the rule cluster. Subsequently, the authors analyze which of seven various quality indices, which they use for all rules and after removing selected outliers, improve the quality of rule clusters. In the experimental stage, the authors use six different knowledge bases. The best results (the most often the clusters quality was improved) are achieved for two outlier detection algorithms LOF and COF.

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19

Raby, Rebecca. "Frustrated, Resigned, Outspoken: Students' Engagement with School Rules and Some Implications for Participatory Citizenship." International Journal of Children's Rights 16, no. 1 (2008): 77–98. http://dx.doi.org/10.1163/092755608x267148.

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AbstractSchool rules are frequently presented as fostering responsibility, respect and self-discipline, yet it is rare for them to discuss students' participation or rights. Drawing on data from nine focus groups with secondary students within a southern region of Ontario, Canada, this paper investigates students' reactions to school rules, particularly in terms of participation in their creation, appeal or challenge. While students often negotiated rules with their teachers, for the most part students had little sense of themselves as able to influence the rules beyond either obedience or rule-breaking. The second half of this paper focuses on student subjectivity. While students sometimes felt able to negotiate the rules through positioning themselves as workers or students in the future, or as teenagers in the process of development, it was when they identified themselves as social actors and rights holders in the present that they were most able to challenge school rules they found to be unfair.

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20

Huyard, Caroline. "Who rules rare disease associations? A framework to understand their action." Sociology of Health & Illness 31, no. 7 (November 2009): 979–93. http://dx.doi.org/10.1111/j.1467-9566.2009.01177.x.

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21

Almasi, Mehrdad, and Mohammad Saniee Abadeh. "Rare-PEARs: A new multi objective evolutionary algorithm to mine rare and non-redundant quantitative association rules." Knowledge-Based Systems 89 (November 2015): 366–84. http://dx.doi.org/10.1016/j.knosys.2015.07.016.

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22

McNicol, Suzanne B. "A Hard Look at Holism and Consequentialism in Hard Cases." Federal Law Review 15, no. 3 (September 1985): 169–205. http://dx.doi.org/10.1177/0067205x8501500302.

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In any field of law … there may arise the rare “landmark” case in which a court, usually a final appellate court, concludes that the circumstances are such as to entitle and oblige it to reassess the content of some rule or set of rules in the context of current social conditions, standards and demands and to change or reverse the direction of the development of the law.1

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23

Olmo, Juan Luis, José Raúl Romero, and Sebastián Ventura. "Single and multi-objective ant programming for mining interesting rare association rules." International Journal of Hybrid Intelligent Systems 11, no. 3 (August 27, 2014): 197–209. http://dx.doi.org/10.3233/his-140195.

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24

Aliev, T. M., M. Savci, A. Özpineci, and H. Koru. "Rare decay, two Higgs doublet model, and light cone QCD sum rules." Physics Letters B 410, no. 2-4 (October 1997): 216–28. http://dx.doi.org/10.1016/s0370-2693(97)00968-4.

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25

McLaren, Juliet, and Jane M. Gillis. "Is This Rule Necessary? A Discussion of New Rules for Rare Serials." Cataloging & Classification Quarterly 43, no. 1 (October 23, 2006): 39–52. http://dx.doi.org/10.1300/j104v43n01_04.

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26

Jo, Takeo, and Arata Tanaka. "Selection Rules in X-Ray Second Order Optical Processes for Rare Earths." Journal of the Physical Society of Japan 66, no. 2 (February 15, 1997): 485–92. http://dx.doi.org/10.1143/jpsj.66.485.

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27

Luna, J. M., J. R. Romero, and S. Ventura. "On the adaptability of G3PARM to the extraction of rare association rules." Knowledge and Information Systems 38, no. 2 (February 9, 2013): 391–418. http://dx.doi.org/10.1007/s10115-012-0591-9.

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28

Tong, Yu Jun, Jun Zhou, Wen Ge Xie, and Dan Jia. "Research and Application of an Enhanced Data Mining Algorithm in Virtual Manufacturing Technology." Advanced Materials Research 299-300 (July 2011): 840–43. http://dx.doi.org/10.4028/www.scientific.net/amr.299-300.840.

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Association rules mining is an important branch of data mining. Apriori algorithm is a classical algorithm of mining association rules. Based on the original Apriori algorithm an improved Apriori algorithm is analyzed according to the multiple minimum supports and support difference constraint. An experiment has been conducted and the results showed that the new algorithm can not only mine out the association rules to meet the demands of multiple minimum supports, but also mine out the rare but potentially profitable items’ association rules.

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29

Liu, Yu Yan, Xing Qian Li, and Zi Li Jin. "Based on CSP Technics, the Experimental Research of Rare Earth Steel Hot-Rolled Deformation Behaviors." Advanced Materials Research 295-297 (July 2011): 1267–73. http://dx.doi.org/10.4028/www.scientific.net/amr.295-297.1267.

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Based on CSP technics, using Gleeble1500-D hot simulation machine, making the single, dual, multi-pass compression experiment of Q345B steel with rare earth Nd respectively, different deformation conditions influencing Q345B steel of recrystallization behavior and the microstructure evolution rule in the hot rolling process have been studied. The results show that: the single, dual-pass experiments of Q345B steel with rare earth Nd are according with general experimental rules. According to single, dual-pass results, we establish multi-pass compression project. In that project, the grain samples with rare earth element Nd are finer than others. It explains that appending rare earth Nd has the obvious function of refining grains. At the same time, the degree of refining grains is different in the different project. It explains that in order to obtain fine grains, we should choose feat technics. By contrast, we can educe that the grains are more fine and uniform in a project.

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30

Bhardwaj, Ankit, Vivek Singh, Kaveri Kapoor, and Anil Kem. "Adrenal crisis: a rare endocrine emergency with challenging diagnosis." International Journal of Basic & Clinical Pharmacology 9, no. 10 (September 22, 2020): 1612. http://dx.doi.org/10.18203/2319-2003.ijbcp20204107.

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Adrenal crisis is a rare life-threatening medical endocrine emergency with non-specific insidious symptoms and challenging diagnosis. An appropriate timely diagnosis and treatment can save life. Although most doctors are educated by “sick day rules,” but are reluctant to start glucocorticoids, increase doses or switch to parental injections. Our case report highlights various aspect of adrenal crisis.

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31

Sharma, Sachin, and Shaveta Bhatia. "A study of frequent itemset mining techniques." International Journal of Engineering & Technology 6, no. 4 (October 14, 2017): 141. http://dx.doi.org/10.14419/ijet.v6i4.8300.

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Frequent item set is the most crucial and expensive task for the industry today. It is the task of mining the information from different sources and a key approach in Data Mining. Frequent item sets satisfying the minimum threshold can be discovered. Association rules are extracted from frequent item sets. The Association rules are affected by the minimum support value entered by the user may be considered as Positive or negative. There may be some other Association rules, which involve the rare item sets. Various methods have been used by researchers for generating the Association Rules. In this paper, our aim is to study various techniques to generate the Association rules.

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32

Kennedy, Gerrard J. "Rule 2.1 of Ontario’s Rules of Civil Procedure: Responding to Vexatious Litigation While Advancing Access to Justice?" Windsor Yearbook of Access to Justice 35 (May 30, 2018): 243–303. http://dx.doi.org/10.22329/wyaj.v35i0.5691.

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This article analyzes the first three years of the operation of Rule 2.1 of Ontario’s Rules of Civil Procedure (the “Rule”), which allows a court to very summarily dismiss litigation that is “on its face” frivolous, vexatious, and/or abusive. The author explores the history of and rationale for the Rule, in the context of the access to justice crisis in Ontario, and in light of the perceived inadequacy of alternative mechanisms for addressing the dangers raised by vexatious litigants. He then reviews all 190 Rule 2.1 decisions decided between July 1, 2014 and June 30, 2017, with the goal to provide guidance for future lawyers and judges considering using the Rule. This is followed by an analysis of the effects on access to justice of the Rule, in terms of providing speedy and cost-efficient resolution of actions on their merits. The author concludes by considering how the Rule should be used in the future – doctrinally, institutionally, and ethically. His conclusions are hopeful. The Rule is powerful, and its use should prompt some pause in judges and lawyers. By and large, however, the Rule has been very well employed. It has resulted in immense savings of time and financial expense and many cases model fairness to vulnerable parties. In rare instances where the Rule’s (attempted) use has been inappropriate, costs in terms of delay and financial expense are usually minimal. The Rule is ultimately an inspiring example of how civil procedure can be amended to facilitate access to justice.

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33

Barakat, Rami Mohamed Bakr, Simone Garzon, Antonio Simone Laganà, Massimo Franchi, and Fabio Ghezzi. "Fetus-in-fetu: a rare condition that requires common rules for its definition." Archives of Gynecology and Obstetrics 302, no. 6 (June 7, 2019): 1541–43. http://dx.doi.org/10.1007/s00404-019-05211-y.

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34

Kalanov, V. P., V. M. Milenin, G. Ju Panasjuk, and N. A. Timofeev. "Similarity rules for low-pressure gas discharges in a metal + rare gas mixture." Physics Letters A 126, no. 5-6 (January 1988): 336–40. http://dx.doi.org/10.1016/0375-9601(88)90846-8.

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35

Rillig, Matthias C., Milos Bielcik, V. Bala Chaudhary, Leonie Grünfeld, Stefanie Maaß, India Mansour, Masahiro Ryo, and Stavros D. Veresoglou. "Ten simple rules for increased lab resilience." PLOS Computational Biology 16, no. 11 (November 19, 2020): e1008313. http://dx.doi.org/10.1371/journal.pcbi.1008313.

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When running a lab we do not think about calamities, since they are rare events for which we cannot plan while we are busy with the day-to-day management and intellectual challenges of a research lab. No lab team can be prepared for something like a pandemic such as COVID-19, which has led to shuttered labs around the globe. But many other types of crises can also arise that labs may have to weather during their lifetime. What can researchers do to make a lab more resilient in the face of such exterior forces? What systems or behaviors could we adjust in ‘normal’ times that promote lab success, and increase the chances that the lab will stay on its trajectory? We offer 10 rules, based on our current experiences as a lab group adapting to crisis.

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36

Bala, Renu, and Saroj Ratnoo. "A Genetic Algorithm Approach for Discovering Tuned Fuzzy Classification Rules with Intra- and Inter-Class Exceptions." Journal of Intelligent Systems 25, no. 2 (April 1, 2016): 263–82. http://dx.doi.org/10.1515/jisys-2015-0136.

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AbstractFuzzy rule-based systems (FRBSs) are proficient in dealing with cognitive uncertainties like vagueness and ambiguity imperative to real-world decision-making situations. Fuzzy classification rules (FCRs) based on fuzzy logic provide a framework for a flexible human-like reasoning involving linguistic variables. Appropriate membership functions (MFs) and suitable number of linguistic terms – according to actual distribution of data – are useful to strengthen the knowledge base (rule base [RB]+ data base [DB]) of FRBSs. An RB is expected to be accurate and interpretable, and a DB must contain appropriate fuzzy constructs (type of MFs, number of linguistic terms, and positioning of parameters of MFs) for the success of any FRBS. Moreover, it would be fascinating to know how a system behaves in some rare/exceptional circumstances and what action ought to be taken in situations where generalized rules cease to work. In this article, we propose a three-phased approach for discovery of FCRs augmented with intra- and inter-class exceptions. A pre-processing algorithm is suggested to tune DB in terms of the MFs and number of linguistic terms for each attribute of a data set in the first phase. The second phase discovers FCRs employing a genetic algorithm approach. Subsequently, intra- and inter-class exceptions are incorporated in the rules in the third phase. The proposed approach is illustrated on an example data set and further validated on six UCI machine learning repository data sets. The results show that the approach has been able to discover more accurate, interpretable, and interesting rules. The rules with intra-class exceptions tell us about the unique objects of a category, and rules with inter-class exceptions enable us to take a right decision in the exceptional circumstances.

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37

Han, Dae-Young, Dae-In Kim, Jae-In Kim, Myung-Jin Song, and Bu-Hyun Hwang. "Finding Association Rules based on the Significant Rare Relation of Events with Time Attribute." KIPS Transactions:PartD 16D, no. 5 (October 31, 2009): 691–700. http://dx.doi.org/10.3745/kipstd.2009.16d.5.691.

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38

Iyer, V., S. Shetty, and S. S. Iyengar. "STATISTICAL METHODS IN AI: RARE EVENT LEARNING USING ASSOCIATIVE RULES AND HIGHER-ORDER STATISTICS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-4/W2 (July 10, 2015): 119–30. http://dx.doi.org/10.5194/isprsannals-ii-4-w2-119-2015.

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Rare event learning has not been actively researched since lately due to the unavailability of algorithms which deal with big samples. The research addresses spatio-temporal streams from multi-resolution sensors to find actionable items from a perspective of real-time algorithms. This computing framework is independent of the number of input samples, application domain, labelled or label-less streams. A sampling overlap algorithm such as Brooks-Iyengar is used for dealing with noisy sensor streams. We extend the existing noise pre-processing algorithms using Data-Cleaning trees. Pre-processing using ensemble of trees using bagging and multi-target regression showed robustness to random noise and missing data. As spatio-temporal streams are highly statistically correlated, we prove that a temporal window based sampling from sensor data streams converges after n samples using Hoeffding bounds. Which can be used for fast prediction of new samples in real-time. The Data-cleaning tree model uses a nonparametric node splitting technique, which can be learned in an iterative way which scales linearly in memory consumption for any size input stream. The improved task based ensemble extraction is compared with non-linear computation models using various SVM kernels for speed and accuracy. We show using empirical datasets the explicit rule learning computation is linear in time and is only dependent on the number of leafs present in the tree ensemble. The use of unpruned trees (<i>t</i>) in our proposed ensemble always yields minimum number (<i>m</i>) of leafs keeping pre-processing computation to <i>n</i> × <i>t</i> log <i>m</i> compared to <i>N<sup>2</sup></i> for Gram Matrix. We also show that the task based feature induction yields higher Qualify of Data (QoD) in the feature space compared to kernel methods using Gram Matrix.

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39

Napolitano, Michael G., Matthieu Landon, Christopher J. Gregg, Marc J. Lajoie, Lakshmi Govindarajan, Joshua A. Mosberg, Gleb Kuznetsov, et al. "Emergent rules for codon choice elucidated by editing rare arginine codons in Escherichia coli." Proceedings of the National Academy of Sciences 113, no. 38 (September 6, 2016): E5588—E5597. http://dx.doi.org/10.1073/pnas.1605856113.

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The degeneracy of the genetic code allows nucleic acids to encode amino acid identity as well as noncoding information for gene regulation and genome maintenance. The rare arginine codons AGA and AGG (AGR) present a case study in codon choice, with AGRs encoding important transcriptional and translational properties distinct from the other synonymous alternatives (CGN). We created a strain of Escherichia coli with all 123 instances of AGR codons removed from all essential genes. We readily replaced 110 AGR codons with the synonymous CGU codons, but the remaining 13 “recalcitrant” AGRs required diversification to identify viable alternatives. Successful replacement codons tended to conserve local ribosomal binding site-like motifs and local mRNA secondary structure, sometimes at the expense of amino acid identity. Based on these observations, we empirically defined metrics for a multidimensional “safe replacement zone” (SRZ) within which alternative codons are more likely to be viable. To evaluate synonymous and nonsynonymous alternatives to essential AGRs further, we implemented a CRISPR/Cas9-based method to deplete a diversified population of a wild-type allele, allowing us to evaluate exhaustively the fitness impact of all 64 codon alternatives. Using this method, we confirmed the relevance of the SRZ by tracking codon fitness over time in 14 different genes, finding that codons that fall outside the SRZ are rapidly depleted from a growing population. Our unbiased and systematic strategy for identifying unpredicted design flaws in synthetic genomes and for elucidating rules governing codon choice will be crucial for designing genomes exhibiting radically altered genetic codes.

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40

Wei, L. M., P. Li, and K. T. Tang. "Iterative combining rules for the van der Waals potentials of mixed rare gas systems." Chemical Physics Letters 675 (May 2017): 40–45. http://dx.doi.org/10.1016/j.cplett.2017.02.066.

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41

Kharkongor, Carynthia, and Bhabesh Nath. "Itemset Representation and Mining the Rules for Huntington’s Dataset." Emerging Science Journal 5, no. 3 (June 1, 2021): 380–91. http://dx.doi.org/10.28991/esj-2021-01284.

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Association rule mining does not restrict to market basket application but it is also employed in many applications such as health, industrial, network domain and etc. In this paper, an association mining algorithm is applied to the health management domain. It helps in the decision making by producing the rules for the early detection of the disease. By checking the personal details and symptoms of the patient, association rule mining will help in prediction and diagnosing the disease at an early stage. The dataset used in this experiment is the Huntington Disease (HD) dataset, which is one of the rare diseases. The dataset needs to be stored in the memory for the computation and generation of rules. Storing the items in the memory will take 4 bytes if the array data structure is used. Furthermore, if the dataset is very large, storing each and every detail in the memory becomes speculative. It is also not cost-effective and consumes a lot of resources. One of the solutions is to present the itemset in such a way that the memory consumed is concise. The items are represented using the set representation that takes less time and memory as compared to the traditional methods. The dataset is mine using the Apriori Algorithm which produces only those itemsets which are more frequent or have a high probability of occurrence. The algorithm gives a prior knowledge of the frequent itemsets. Then, the rules will be generated from these frequent itemsets. The memory and time consumption using the set representation is compared with the array representation of itemsets. Doi: 10.28991/esj-2021-01284 Full Text: PDF

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Marovic, Paul, Paul Edmond Smith, and Drew Slimmon. "Isolated Tibialis Posterior Muscle Strain: A rare sporting injury." International Journal of Sport, Exercise and Health Research 4, no. 2 (December 30, 2020): 44–45. http://dx.doi.org/10.31254/sportmed.4202.

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We present the case of an isolated tibialis posterior muscle strain in an Australian Rules Football (AFL) player, an injury not previously described in the medical literature. The elite footballer presented with calf tightness following a game of AFL. The clinical history, examination findings and treatment regime followed a course similar to more typical “calf strains” involving the gastrocnemius and soleus muscles, however Magnetic Resonance Imaging (MRI) revealed a low grade isolated muscle strain of tibialis posterior. The only inciting factor was the use of new football boots. This novel case will alert radiologists and sports physicians to a new potential source of calf pain in athletes.

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Kim, Minjung, and Do Hyun Park. "A model and the behavioral implications of the calculus of consent: The dilemma of public choice before public choice." PLOS ONE 15, no. 12 (December 15, 2020): e0243728. http://dx.doi.org/10.1371/journal.pone.0243728.

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The choice of a group decision-making rule is one of the most important political issues. Buchanan and Tullock have provided a framework for analyzing the optimal k-majority rule from the perspective of “methodological individualism.” They proposed the concept of “external costs” and “decision costs” and argued that the optimal k-majority rule takes place where the sum of these two costs–“total costs”–is minimized. Despite the fact that the approach is widely accepted as a tool for dealing with public decision-making rules, the study of formalizing these two costs in a quantitative manner has been relatively rare. We propose a systematic way of modeling these costs considering the assumptions mentioned by Buchanan and Tullock. We find that the resulting shape of the graphs is generally similar to that of the Buchanan-Tullock model, except for some minor details. Then, using this analytical model, we investigate several factors that could affect Buchanan-Tullock’s two costs and the optimal k-majority rule. We show that “clustering of disadvantages” (social factor) and “loss aversion” (personal factor) could increase external costs in Buchanan-Tullock’s model. These factors can result in a separation between the theoretical and actual optimal k-majority rules. Meanwhile, some recent developments in information and communication technologies can not only decrease decision costs, but also increase the same costs simultaneously through amplified “group polarization” (technological factor). If the effect of the former is not the same as that of the latter, this leads to a difference in optimal k-majority rules as well. These discrepancies bring us to the dilemma of “public choice before public choice.”

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Cheng, Liang-Liang, Ke Ju, Rui-Lie Cai, and Chang Xu. "The use of one-stage meta-analytic method based on individual participant data for binary adverse events under the rule of three: a simulation study." PeerJ 7 (January 23, 2019): e6295. http://dx.doi.org/10.7717/peerj.6295.

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Objective In evidence synthesis practice, dealing with binary rare adverse events (AEs) is a challenging problem. The pooled estimates for rare AEs through traditional inverse variance (IV), Mantel-Haenszel (MH), and Yusuf-Peto (Peto) methods are suboptimal, as the biases tend to be large. We proposed the “one-stage” approach based on multilevel variance component logistic regression (MVCL) to handle this problem. Methods We used simulations to generate trials of individual participant data (IPD) with a series of predefined parameters. We compared the performance of the MVCL “one-stage” approach and the five classical methods (fixed/random effect IV, fixed/random effect MH, and Peto) for rare binary AEs under different scenarios, which included different sample size setting rules, effect sizes, between-study heterogeneity, and numbers of studies in each meta-analysis. The percentage bias, mean square error (MSE), coverage probability, and average width of the 95% confidence intervals were used as performance indicators. Results We set 52 scenarios and each scenario was simulated 1,000 times. Under the rule of three (a sample size setting rule to ensure a 95% chance of detecting at least one AE case), the MVCL “one-stage” IPD method had the lowest percentage bias in most of the situations and the bias remained at a very low level (<10%), when compared to IV, MH, and Peto methods. In addition, the MVCL “one-stage” IPD method generally had the lowest MSE and the narrowest average width of 95% confidence intervals. However, it did not show better coverage probability over the other five methods. Conclusions The MVCL “one-stage” IPD meta-analysis is a useful method to handle binary rare events and superior compared to traditional methods under the rule of three. Further meta-analyses may take account of the “one-stage” IPD method for pooling rare event data.

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Kilby, Charles. "China's Rare Earth Trade: Health and the Environment." China Quarterly 218 (March 18, 2014): 540–50. http://dx.doi.org/10.1017/s0305741014000320.

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AbstractRare earth elements (REE) captured a startled world's attention during the 2010 Diaoyu/Senkaku Islands crisis, when it appeared that China withheld access to them during its border dispute with Japan. China asserts that its sovereign right to environmental regulation and national production quotas is unassailable. However, China's trade measures appear to be inconsistent with WTO rules, as well as with environmental protection and conservation, since they incentivize illegal mining and smuggling practices. In an upcoming case (DS431), the United States, the European Union, Japan and 16 third parties will argue before the WTO that China's trade measures on rare earths, tungsten and molybdenum constitute discriminatory behaviour and are illegal. This raises the question of whether China is inappropriately using the environment as a defence against allegations that its rare earth trade policies are in violation of its WTO obligations.

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Geist, Verena, Christa Illibauer, Christine Natschläger, and Robert Hutter. "Supporting Customizable Business Process Models Using Graph Transformation Rules." International Journal of Information System Modeling and Design 7, no. 3 (July 2016): 51–71. http://dx.doi.org/10.4018/ijismd.2016070103.

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Business Process customization is an active research area in the process management field, dealing with variations/commonalities among processes of a given process family and runtime adaptations of single process instances. Many theoretical approaches have been suggested in the last years; however, practical implementations are rare and limited in their functionality. In this article, a new approach is proposed for capturing customizable process models based on well-known graph transformation techniques and with focus on practical aspects like definition of variation points, linking and propagation of changes, visual highlighting of differences in process variants, and dynamically selecting a specific variant at runtime. The suggested concepts are discussed within case studies, comprising different graph transformation systems for generating process variants supporting (a) variability by restriction, (b) variability by restriction and by extension, and (c) runtime adaptations due to the executing actor. The overall approach is being implemented in the FireStart BPM suite.

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Bashiry, V. "Investigation of the Rare ExclusiveBc*→Dsνν-Decays in the Framework of the QCD Sum Rules." Advances in High Energy Physics 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/503049.

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ExclusiveBc*→Dsνν-decay is studied in the framework of the three-point QCD sum rules approach. The two gluon condensate contributions to the correlation function are calculated and the form factors of this transition are found. The decay width and total branching ratio for this decay are also calculated.

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Koubaa, Rania, Eya Ben Ahmed, and Faiez Gargouri. "Towards an Intelligent OLAP System Facing Sparse Problems." International Journal of Web Portals 6, no. 4 (October 2014): 41–57. http://dx.doi.org/10.4018/ijwp.2014100103.

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Exploring intelligent data stored in data warehouses may efficiently assist the knowledge-seeker in his decision process. Such traced information related to performed analysis by decision-makers on data warehouses are stored in OLAP log files. These files contain useful knowledge about the analysts' preferences. Sometimes, some formulated queries provide no results. Such a dilemma is known as the sparsity problem. In this paper, to overcome this limitation in user-centric data warehouses, the authors focus on a specific class of preferences, namely the conflicting preferences. Indeed, a conflicting preference describes a low frequency preference stored in OLAP log files, so that it is considered as tailored to given analysts. Such preferences are characterized by their rarity. To deal with this issue, the authors introduce a new approach to discover these preferences through mining of rare association rules using a new introduced method for generating the N highest confidence rare association rules. The derived rare preferences will be used to reformulate the launched query avoiding an empty result. The carried out experiments on their built online recruitment data warehouse point out the efficiency of their approach.

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Kuerner, Thomas. "Essential rules and requirements for global clinical trials in rare lung diseases: A sponsor׳s standpoint." Respiratory Investigation 53, no. 1 (January 2015): 2–6. http://dx.doi.org/10.1016/j.resinv.2014.09.001.

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Luna, J. M., C. Romero, J. R. Romero, and S. Ventura. "An evolutionary algorithm for the discovery of rare class association rules in learning management systems." Applied Intelligence 42, no. 3 (November 14, 2014): 501–13. http://dx.doi.org/10.1007/s10489-014-0603-4.

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