Impact of antibiotics as anthropogenic stressor for influencing bacterial evolutionary process – A review

The Islamic Awakening in Malaysia has brought about the consciousness of adopting and practicing the Islamic way of life. The process of implementing the principles of Islam is based on a gradual evolutionary process, rather than a drastic approach. Therefore, the selective implementation of Islamic law has been carried out relatively smoothly. For that reason, various institutions have been established ‒ such as, Islamic universities, Islamic banking and insurance companies, and other Islamic organizations and institutions. The case studies in this article related to Malaysia are: The Pan-Malaysian Islamic Party (PAS), Angkatan Belia Islam Malaysia – ABIM (Malaysian Islamic Youth Movement), and some Islamic institutions, which play important roles in the Islamic Awakening and solidarity in Malaysia. The PAS and ABIM are the prominent Islamic parties and movements, respectively, which can be regarded as the driving force behind the Islamic Awakening in Malaysia. Based on a tridimensional perspective ‒ that is, socioeconomic well-being and the strength of the expansion of Islamic education, and political stability ‒ this study highlights the accomplishment of Islamic Awakening in Malaysia.

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Evolutionary process unveiled by the maximum genetic diversity hypothesis

Hereditas (Beijing) ◽

10.3724/sp.j.1005.2013.00599 ◽

2013 ◽

Vol 35 (5) ◽

pp. 599-606 ◽

Cited By ~ 1

Author(s):

Yi-Min HUANG ◽

Meng-Ying XIA ◽

Shi HUANG

Keyword(s):

Genetic Diversity ◽

Evolutionary Process ◽

Maximum Genetic Diversity

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MySuper: A Stage in an Evolutionary Process

SSRN Electronic Journal ◽

10.2139/ssrn.2537198 ◽

2014 ◽

Cited By ~ 1

Author(s):

Adam Butt ◽

M. Scott Donald ◽

F. Douglas Foster ◽

Susan Thorp ◽

Geoff Warren

Keyword(s):

Evolutionary Process

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A Review of Multi-Objective Evolutionary Based Fuzzy Classifiers

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190410142052 ◽

2020 ◽

Vol 13 (1) ◽

pp. 77-85

Author(s):

Praveen Kumar Dwivedi ◽

Surya Prakash Tripathi

Keyword(s):

Fuzzy Systems ◽

Evolutionary Process ◽

Fuzzy Rule ◽

Fuzzy Classification ◽

Multi Objective Optimization ◽

Fuzzy Classifier ◽

Rule Based ◽

Trade Off ◽

Multi Objective ◽

Rule Based Systems

Background: Fuzzy systems are employed in several fields like data processing, regression, pattern recognition, classification and management as a result of their characteristic of handling uncertainty and explaining the feature of the advanced system while not involving a particular mathematical model. Fuzzy rule-based systems (FRBS) or fuzzy rule-based classifiers (mainly designed for classification purpose) are primarily the fuzzy systems that consist of a group of fuzzy logical rules and these FRBS are unit annexes of ancient rule-based systems, containing the "If-then" rules. During the design of any fuzzy systems, there are two main objectives, interpretability and accuracy, which are conflicting with each another, i.e., improvement in any of those two options causes the decrement in another. This condition is termed as Interpretability –Accuracy Trade-off. To handle this condition, Multi-Objective Evolutionary Algorithms (MOEA) are often applied within the design of fuzzy systems. This paper reviews the approaches to the problem of developing fuzzy systems victimization evolutionary process Multi-Objective Optimization (EMO) algorithms considering ‘Interpretability-Accuracy Trade-off, current research trends and improvement in the design of fuzzy classifier using MOEA in the future scope of authors. Methods: The state-of-the-art review has been conducted for various fuzzy classifier designs, and their optimization is reviewed in terms of multi-objective. Results: This article reviews the different Multi-Objective Optimization (EMO) algorithms in the context of Interpretability -Accuracy tradeoff during fuzzy classification. Conclusion: The evolutionary multi-objective algorithms are being deployed in the development of fuzzy systems. Improvement in the design using these algorithms include issues like higher spatiality, exponentially inhabited solution, I-A tradeoff, interpretability quantification, and describing the ability of the system of the fuzzy domain, etc. The focus of the authors in future is to find out the best evolutionary algorithm of multi-objective nature with efficiency and robustness, which will be applicable for developing the optimized fuzzy system with more accuracy and higher interpretability. More concentration will be on the creation of new metrics or parameters for the measurement of interpretability of fuzzy systems and new processes or methods of EMO for handling I-A tradeoff.

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An Evolutionary Process—The Federalization of Corporate Governance

10.1093/oso/9780199934546.003.0001 ◽

2018 ◽

Author(s):

Marc I. Steinberg

Keyword(s):

Corporate Governance ◽

Historical Perspective ◽

Evolutionary Process ◽

Stock Exchanges ◽

Federal Law ◽

Sarbanes Oxley

This chapter provides an overview regarding the federalization of corporate governance as an evolutionary process. From this perspective, the chapter examines both state and federal law that impact corporate governance. As the chapter explains, from a historical perspective, the states emerged as the primary regulator of corporate governance. Today, Delaware has emerged as the preeminent state where publicly-held corporations elect to incorporate. Nonetheless, federal law, even from a traditional perspective, impacted corporate governance, such as the SEC’s shareholder proposal rule adopted over 75 years ago. With the enactment of the Sarbanes-Oxley Act of 2002, the Dodd-Frank Act of 2010, SEC rules adopted under the authority of these statutes, and the emergence of stricter substantive listing requirements mandated by the national stock exchanges, federal law principles are now firmly established.

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Distinguishing linear and branched evolution given single-cell DNA sequencing data of tumors

Algorithms for Molecular Biology ◽

10.1186/s13015-021-00194-5 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Leah L. Weber ◽

Mohammed El-Kebir

Keyword(s):

Dna Sequencing ◽

Single Cell ◽

Evolutionary Process ◽

Treatment Decision ◽

Real Data ◽

Current Data ◽

Fast Method ◽

Sequencing Data ◽

Evolutionary Trajectory ◽

Cancer Types

Abstract Background Cancer arises from an evolutionary process where somatic mutations give rise to clonal expansions. Reconstructing this evolutionary process is useful for treatment decision-making as well as understanding evolutionary patterns across patients and cancer types. In particular, classifying a tumor’s evolutionary process as either linear or branched and understanding what cancer types and which patients have each of these trajectories could provide useful insights for both clinicians and researchers. While comprehensive cancer phylogeny inference from single-cell DNA sequencing data is challenging due to limitations with current sequencing technology and the complexity of the resulting problem, current data might provide sufficient signal to accurately classify a tumor’s evolutionary history as either linear or branched. Results We introduce the Linear Perfect Phylogeny Flipping (LPPF) problem as a means of testing two alternative hypotheses for the pattern of evolution, which we prove to be NP-hard. We develop Phyolin, which uses constraint programming to solve the LPPF problem. Through both in silico experiments and real data application, we demonstrate the performance of our method, outperforming a competing machine learning approach. Conclusion Phyolin is an accurate, easy to use and fast method for classifying an evolutionary trajectory as linear or branched given a tumor’s single-cell DNA sequencing data.

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Validation of Automated Chromosome Recovery in the Reconstruction of Ancestral Gene Order

Algorithms ◽

10.3390/a14060160 ◽

2021 ◽

Vol 14 (6) ◽

pp. 160

Author(s):

Qiaoji Xu ◽

Lingling Jin ◽

James H. Leebens-Mack ◽

David Sankoff

Keyword(s):

Phylogenetic Tree ◽

Gene Order ◽

Evolutionary Process ◽

Gene Content ◽

Ancestral Genome ◽

Maximum Weight ◽

Ancestral Gene ◽

Maximum Weight Matching

The RACCROCHE pipeline reconstructs ancestral gene orders and chromosomal contents of the ancestral genomes at all internal vertices of a phylogenetic tree. The strategy is to accumulate a very large number of generalized adjacencies, phylogenetically justified for each ancestor, to produce long ancestral contigs through maximum weight matching. It constructs chromosomes by counting the frequencies of ancestral contig co-occurrences on the extant genomes, clustering these for each ancestor and ordering them. The main objective of this paper is to closely simulate the evolutionary process giving rise to the gene content and order of a set of extant genomes (six distantly related monocots), and to assess to what extent an updated version of RACCROCHE can recover the artificial ancestral genome at the root of the phylogenetic tree relating to the simulated genomes.

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