scholarly journals SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Junhui Qiu ◽  
Qi Zhou ◽  
Weicai Ye ◽  
Qianjun Chen ◽  
Yun-Juan Bao
Keyword(s):  
Clustering Algorithm ◽  
Spatial Clustering ◽  
Selection Process ◽  
Null Distribution ◽  
Concordance Rate ◽  
Distribution Model ◽  
Population Subdivision ◽  
Evolutionary Mechanisms ◽  
High Level ◽  
The Impact

Abstract Background The gene-specific sweep is a selection process where an advantageous mutation along with the nearby neutral sites in a gene region increases the frequency in the population. It has been demonstrated to play important roles in ecological differentiation or phenotypic divergence in microbial populations. Therefore, identifying gene-specific sweeps in microorganisms will not only provide insights into the evolutionary mechanisms, but also unravel potential genetic markers associated with biological phenotypes. However, current methods were mainly developed for detecting selective sweeps in eukaryotic data of sparse genotypes and are not readily applicable to prokaryotic data. Furthermore, some challenges have not been sufficiently addressed by the methods, such as the low spatial resolution of sweep regions and lack of consideration of the spatial distribution of mutations. Results We proposed a novel gene-centric and spatial-aware approach for identifying gene-specific sweeps in prokaryotes and implemented it in a python tool SweepCluster. Our method searches for gene regions with a high level of spatial clustering of pre-selected polymorphisms in genotype datasets assuming a null distribution model of neutral selection. The pre-selection of polymorphisms is based on their genetic signatures, such as elevated population subdivision, excessive linkage disequilibrium, or significant phenotype association. Performance evaluation using simulation data showed that the sensitivity and specificity of the clustering algorithm in SweepCluster is above 90%. The application of SweepCluster in two real datasets from the bacteria Streptococcus pyogenes and Streptococcus suis showed that the impact of pre-selection was dramatic and significantly reduced the uninformative signals. We validated our method using the genotype data from Vibrio cyclitrophicus, the only available dataset of gene-specific sweeps in bacteria, and obtained a concordance rate of 78%. We noted that the concordance rate could be underestimated due to distinct reference genomes and clustering strategies. The application to the human genotype datasets showed that SweepCluster is also applicable to eukaryotic data and is able to recover 80% of a catalog of known sweep regions. Conclusion SweepCluster is applicable to a broad category of datasets. It will be valuable for detecting gene-specific sweeps in diverse genotypic data and provide novel insights on adaptive evolution.

scholarly journals SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

2021 ◽  
Author(s):  
Junhui Qiu ◽  
Qi Zhou ◽  
Weicai Ye ◽  
Qianjun Chen ◽  
Yun-Juan Bao
Keyword(s):  
Clustering Algorithm ◽  
Dynamic Range ◽  
Spatial Clustering ◽  
Selection Process ◽  
Null Distribution ◽  
Concordance Rate ◽  
Distribution Model ◽  
Population Subdivision ◽  
Evolutionary Mechanisms ◽  
The Impact

AbstractBackgroundThe gene-specific sweep is a selection process where an advantageous mutation along with the nearby neutral sites in a gene region increases the frequency in the population. It has been demonstrated to play important roles in ecological differentiation or phenotypic divergence in microbial populations. Therefore, identifying gene-specific sweeps in microorganisms will not only provide insights into the evolutionary mechanisms, but also unravel potential genetic markers associated with biological phenotypes. However, current methods were mainly developed for detecting selective sweeps in eukaryotic data of sparse genotypes and are not readily applicable to prokaryotic data. Furthermore, some challenges have not been sufficiently addressed by the methods, such as the low spatial resolution of sweep regions and lack of consideration of the spatial distribution of mutations.ResultsWe proposed a novel gene-centric and spatial-aware approach for identifying gene-specific sweeps in prokaryotes and implemented it in a python tool SweepCluster. Our method searches for gene regions with a high level of spatial clustering of pre-selected polymorphisms in genotype datasets assuming a null distribution model of neutral selection. The pre-selection of polymorphisms is based on their genetic signatures, such as elevated population subdivision, excessive linkage disequilibrium, or significant phenotype association. Performance evaluation using simulation data showed that the accuracy and sensitivity of the clustering algorithm in SweepCluster is above 90%. The application of SweepCluster in two real datasets from the bacteria Streptococcus pyogenes and Streptococcus suis showed that the impact of pre-selection was dramatic and significantly reduced the uninformative signals. We validated our method using the genotype data from Vibrio cyclitrophicus, the only available dataset of gene-specific sweeps in bacteria, and obtained a concordance rate of 78%. We noted that the concordance rate could be underestimated due to distinct reference genomes and clustering strategies. The application to the human genotype datasets showed that SweepCluster is also applicable to eukaryotic data and recovered the known sweep regions in a wide dynamic range of pre-selection parameters.ConclusionsSweepCluster is applicable to a broad category of datasets. It will be valuable for detecting gene-specific sweeps in diverse genotypic data and provide novel insights on adaptive evolution.

scholarly journals A Quantification Method for Supraharmonic Emissions Based on Outlier Detection Algorithms

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6404
Author(s):  
Hui Zhou ◽  
Zesen Gui ◽  
Jiang Zhang ◽  
Qun Zhou ◽  
Xueshan Liu ◽  
...  
Keyword(s):  
Outlier Detection ◽  
Clustering Algorithm ◽  
Spatial Clustering ◽  
Skewed Distribution ◽  
Distribution Model ◽  
Distribution Data ◽  
Original Spectrum ◽  
Detection Algorithms ◽  
Quantification Method ◽  
Dbscan Clustering

Based on outlier detection algorithms, a feasible quantification method for supraharmonic emission signals is presented. It is designed to tackle the requirements of high-resolution and low data volume simultaneously in the frequency domain. The proposed method was developed from the skewed distribution data model and the self-tuning parameters of density-based spatial clustering of applications with noise (DBSCAN) algorithm. Specifically, the data distribution of the supraharmonic band was analyzed first by the Jarque–Bera test. The threshold was determined based on the distribution model to filter out noise. Subsequently, the DBSCAN clustering algorithm parameters were adjusted automatically, according to the k-dist curve slope variation and the dichotomy parameter seeking algorithm, followed by the clustering. The supraharmonic emission points were analyzed as outliers. Finally, simulated and experimental data were applied to verify the effectiveness of the proposed method. On the basis of the detection results, a spectrum with the same resolution as the original spectrum was obtained. The amount of data declined by more than three orders of magnitude compared to the original spectrum. The presented method will benefit the analysis of quantification for the amplitude and frequency of supraharmonic emissions.

scholarly journals Clinical evaluation of a novel point-of-care assay to detect Mycoplasma pneumoniae and associated macrolide resistant mutations

2021 ◽  
Author(s):  
Toshihiko Kakiuchi ◽  
Ippei Miyata ◽  
Reiji Kimura ◽  
Goh Shimomura ◽  
Kunihisa Shimomura ◽  
...  
Keyword(s):  
Mycoplasma Pneumoniae ◽  
Clinical Evaluation ◽  
Respiratory Infections ◽  
Point Of Care ◽  
Community Acquired Pneumonia ◽  
Concordance Rate ◽  
Medical Institutions ◽  
Quenching Probe ◽  
High Level ◽  
The Impact

The recent increase in macrolide-resistant Mycoplasma pneumoniae (M. pneumoniae) in Asia has become a continuing problem. A point-of-care testing method that can quickly detect M. pneumoniae and macrolide-resistant mutations (MR mutations) is critical to proper antimicrobial use. Smart Gene TM (MIZUHO MEDY Co., Ltd. Tosu-City, Saga, Japan) is a compact and inexpensive fully automatic gene analyzer that combines amplification with polymerase chain reaction (PCR) and the quenching probe method to specify the gene and MR mutations simultaneously. We performed a clinical evaluation of this device and its reagents on pediatric patients with M. pneumoniae-suspected respiratory infections and evaluated the impact of the assay on antimicrobial selection. Using real-time PCR as a comparison control, the sensitivity of Smart Gene TM was 97.8% (44/45), its specificity was 93.3% (98/105) and its overall concordance rate was 94.7% (142/150). The overall concordance rate of Smart Gene TM diagnosis of MR mutations in comparison with sequence analysis was 100% (48/48). The ratio of MR mutations was significantly higher at high-level medical institutions than at a primary medical clinic (P = 0.023), and changes in antibiotic therapy to drugs other than macrolides was significantly more common in patients with MR mutations (P = 0.00024). Smart Gene TM demonstrated excellent utility in the diagnosis of M. pneumoniae and the selection of appropriate antimicrobials for MR mutations at primary medical institutions, which play a central role in community-acquired pneumonia care. The use of this device may reduce referrals to high-level medical institutions for respiratory infections, thereby reducing the medical and economic burden on patients.

scholarly journals A belief revision approach for argumentation-based negotiation agents

2015 ◽  
Vol 25 (3) ◽  
pp. 455-470 ◽  
Author(s):  
Pablo Pilotti ◽  
Ana Casali ◽  
Carlos Chesñevar
Keyword(s):  
Belief Revision ◽  
Belief Change ◽  
Selection Process ◽  
Formal Proof ◽  
Negotiation Process ◽  
Multi Agent Systems ◽  
Conflicting Objectives ◽  
Negotiation Agents ◽  
High Level ◽  
The Impact

Abstract Negotiation is an interaction that happens in multi-agent systems when agents have conflicting objectives and must look for an acceptable agreement. A typical negotiating situation involves two agents that cannot reach their goals by themselves because they do not have some resources they need or they do not know how to use them to reach their goals. Therefore, they must start a negotiation dialogue, taking also into account that they might have incomplete or wrong beliefs about the other agent’s goals and resources. This article presents a negotiating agent model based on argumentation, which is used by the agents to reason on how to exchange resources and knowledge in order to achieve their goals. Agents that negotiate have incomplete beliefs about the others, so that the exchange of arguments gives them information that makes it possible to update their beliefs. In order to formalize their proposals in a negotiation setting, the agents must be able to generate, select and evaluate arguments associated with such offers, updating their mental state accordingly. In our approach, we will focus on an argumentation-based negotiation model between two cooperative agents. The arguments generation and interpretation process is based on belief change operations (expansions, contractions and revisions), and the selection process is a based on a strategy. This approach is presented through a high-level algorithm implemented in logic programming. We show various theoretical properties associated with this approach, which have been formalized and proved using Coq, a formal proof management system. We also illustrate, through a case study, the applicability of our approach in order to solve a slightly modified version of the well-known home improvement agents problem. Moreover, we present various simulations that allow assessing the impact of belief revision on the negotiation process.

scholarly journals An Analysis of Selection in Genetic Programming

2021 ◽  
Author(s):  
◽  
Huayang Xie
Keyword(s):  
Genetic Programming ◽  
Population Size ◽  
Selection Pressure ◽  
Clustering Algorithm ◽  
Selection Process ◽  
Fitness Evaluation ◽  
Parent Selection ◽  
Size Limitation ◽  
Tournament Selection ◽  
The Impact

<p>This thesis presents an analysis of the selection process in tree-based Genetic Programming (GP), covering the optimisation of both parent and offspring selection, and provides a detailed understanding of selection and guidance on how to improve GP search effectively and efficiently. The first part of the thesis providesmodels and visualisations to analyse selection behaviour in standard tournament selection, clarifies several issues in standard tournament selection, and presents a novel solution to automatically and dynamically optimise parent selection pressure. The fitness evaluation cost of parent selection is then addressed and some cost-saving algorithms introduced. In addition, the feasibility of using good predecessor programs to increase parent selection efficiency is analysed. The second part of the thesis analyses the impact of offspring selection pressure on the overall GP search performance. The fitness evaluation cost of offspring selection is then addressed, with investigation of some heuristics to efficiently locate good offspring by constraining crossover point selection structurally through the analysis of the characteristics of good crossover events. The main outcomes of the thesis are three new algorithms and four observations: 1) a clustering tournament selection method is developed to automatically and dynamically tune parent selection pressure; 2) a passive evaluation algorithm is introduced for reducing parent fitness evaluation cost for standard tournament selection using small tournament sizes; 3) a heuristic population clustering algorithm is developed to reduce parent fitness evaluation cost while taking advantage of clustering tournament selection and avoiding the tournament size limitation; 4) population size has little impact on parent selection pressure thus the tournament size configuration is independent of population size; and different sampling replacement strategies have little impact on the selection behaviour in standard tournament selection; 5) premature convergence occurs more often when stochastic elements are removed from both parent and offspring selection processes; 6) good crossover events have a strong preference for whole program trees, and (less strongly) single-node or small subtrees that are at the bottom of parent program trees; 7) the ability of standard GP crossover to generate good offspring is far below what was expected.</p>

scholarly journals An Analysis of Selection in Genetic Programming

2021 ◽  
Author(s):  
◽  
Huayang Xie
Keyword(s):  
Genetic Programming ◽  
Population Size ◽  
Selection Pressure ◽  
Clustering Algorithm ◽  
Selection Process ◽  
Fitness Evaluation ◽  
Parent Selection ◽  
Size Limitation ◽  
Tournament Selection ◽  
The Impact

<p>This thesis presents an analysis of the selection process in tree-based Genetic Programming (GP), covering the optimisation of both parent and offspring selection, and provides a detailed understanding of selection and guidance on how to improve GP search effectively and efficiently. The first part of the thesis providesmodels and visualisations to analyse selection behaviour in standard tournament selection, clarifies several issues in standard tournament selection, and presents a novel solution to automatically and dynamically optimise parent selection pressure. The fitness evaluation cost of parent selection is then addressed and some cost-saving algorithms introduced. In addition, the feasibility of using good predecessor programs to increase parent selection efficiency is analysed. The second part of the thesis analyses the impact of offspring selection pressure on the overall GP search performance. The fitness evaluation cost of offspring selection is then addressed, with investigation of some heuristics to efficiently locate good offspring by constraining crossover point selection structurally through the analysis of the characteristics of good crossover events. The main outcomes of the thesis are three new algorithms and four observations: 1) a clustering tournament selection method is developed to automatically and dynamically tune parent selection pressure; 2) a passive evaluation algorithm is introduced for reducing parent fitness evaluation cost for standard tournament selection using small tournament sizes; 3) a heuristic population clustering algorithm is developed to reduce parent fitness evaluation cost while taking advantage of clustering tournament selection and avoiding the tournament size limitation; 4) population size has little impact on parent selection pressure thus the tournament size configuration is independent of population size; and different sampling replacement strategies have little impact on the selection behaviour in standard tournament selection; 5) premature convergence occurs more often when stochastic elements are removed from both parent and offspring selection processes; 6) good crossover events have a strong preference for whole program trees, and (less strongly) single-node or small subtrees that are at the bottom of parent program trees; 7) the ability of standard GP crossover to generate good offspring is far below what was expected.</p>

ПРАГМАТИЧНИЙ ПОТЕНЦІАЛ НАТИВНОЇ РЕКЛАМИ: ФОРМИ, ТРЕНДИ (НА ПРИКЛАДІ НАТИВНОГО КОНТЕНТУ В СОЦІАЛЬНІЙ МЕРЕЖІ FACEBOOK ЩОДО БРЕНДА ФАКУЛЬТЕТУ ЖУРНАЛІСТИКИ ЗНУ)

2020 ◽  
pp. 113
Author(s):  
V. Kovpak ◽  
N. Trotsenko
Keyword(s):  
Social Network ◽  
Professional Training ◽  
Educational Process ◽  
Communication Strategy ◽  
Student Centered ◽  
Teacher Student ◽  
The Social ◽  
National University ◽  
High Level ◽  
The Impact

<div><p><em>The article analyzes the peculiarities of the format of native advertising in the media space, its pragmatic potential (in particular, on the example of native content in the social network Facebook by the brand of the journalism department of ZNU), highlights the types and trends of native advertising. The following research methods were used to achieve the purpose of intelligence: descriptive (content content, including various examples), comparative (content presentation options) and typological (types, trends of native advertising, in particular, cross-media as an opportunity to submit content in different formats (video, audio, photos, text, infographics, etc.)), content analysis method using Internet services (using Popsters service). And the native code for analytics was the page of the journalism department of Zaporizhzhya National University on the social network Facebook. After all, the brand of the journalism department of Zaporozhye National University in 2019 celebrates its 15th anniversary. The brand vector is its value component and professional training with balanced distribution of theoretical and practical blocks (seven practices), student-centered (democratic interaction and high-level teacher-student dialogue) and integration into Ukrainian and world educational process (participation in grant programs).</em></p></div><p><em>And advertising on social networks is also a kind of native content, which does not appear in special blocks, and is organically inscribed on one page or another and unobtrusively offers, just remembering the product as if «to the word». Popsters service functionality, which evaluates an account (or linked accounts of one person) for 35 parameters, but the main three areas: reach or influence, or how many users evaluate, comment on the recording; true reach – the number of people affected; network score – an assessment of the audience’s response to the impact, or how far the network information diverges (how many share information on this page).</em></p><p><strong><em>Key words:</em></strong><em> nativeness, native advertising, branded content, special project, communication strategy.</em></p>

THE IMPACT OF UKRAINE'S EXCISE DUTY POLICY ON THE TRANSFORMATION PROCESSES OF THE TOBACCO MARKET

2020 ◽  
Vol 2020 (10) ◽  
pp. 19-33
Author(s):  
Nadiia NOVYTSKA ◽  
◽  
Inna KHLIEBNIKOVA ◽  
Keyword(s):  
Structural Changes ◽  
Tax Avoidance ◽  
Transformation Process ◽  
State Regulation ◽  
Tobacco Products ◽  
Excise Duty ◽  
Increasing Demand ◽  
High Level ◽  
The Impact ◽  
Transformation Processes

The market of tobacco products in Ukraine is one of the most dynamic and competitive. It develops under the influence of certain factors that cause structural changes, therefore, the aim of the article is to conduct a comprehensive analysis of transformation processes in the market of tobacco and their alternatives in Ukraine and identify the factors that cause them. The high level of tax burden and the proliferation of alternative products with a potentially lower risk to human health, including heating tobacco products and e-cigarettes, are key factors in the market’s transformation process. Their presence leads to an increase in illicit turnover of tobacco products, which accounts for 6.37% of the market, and the gradual replacement of cigarettes with alternative products, which account for 12.95%. The presence on the market of products that are not taxed or taxed at lower rates is one of the reasons for the reduction of excise duty revenues. According to the results of 2019, the planned indicators of revenues were not met by 23.5%. Other reasons for non-fulfillment of excise duty revenues include: declining dynamics of the tobacco products market; reduction in the number of smokers; reorientation of «cheap whites» cigarette flows from Ukraine to neighboring countries; tax avoidance. Prospects for further research are identified, namely the need to develop measures for state regulation and optimization of excise duty taxation of tobacco products and their alternatives, taking into account the risks to public health and increasing demand of illegal products.

Students’ Management to Increase the Character and Achievement in MAN 2 Banjarnegara

2018 ◽  
Vol 2 ◽  
Author(s):  
Sidik Wibowo Akhmad
Keyword(s):  
Academic Achievement ◽  
Extracurricular Activities ◽  
Selection Process ◽  
Skill Test ◽  
Spare Time ◽  
New Students ◽  
Strong Motivation ◽  
Character Building ◽  
The Impact ◽  
Enrollment Process

The purpose of this study was to describe the students’ management in increasing the character and achievement in MAN 2 Banjarnegara including: (1) the enrollment process of new students, (2) guiding students through discipline, noble character building, academic and non-academic achievement, and (3) the impact of character building and the achievement for students MAN 2 Banjarnegara. This research implemented descriptive qualitative approach. The data collection techniques were in-depth interview, observation, and documentation study. The validity of the data used three criteria; namely credibility, dependability, and conformability. The findings of this study were: The first, the enrollment process of the new students was made a breakthrough during the registration of academic and non-academic achievement of scholarships, the selection process was conducted through the value of official learning reports, certificate of championship/achievement, academic potential test and non-academic, and also the skill test. For the students who passed the selection process were supposed to sign the achievement contract during the learning process at MAN 2 Banjarnegara. The second, the character building was done by the concept of habituation and activities program that were integrated in curricular and extracurricular activities. The third, students who joined the academic and non-academic achievement programs at MAN 2 Banjarnegara had strong motivation, spirit of competition to achieve higher achievement and more focus on self-development and they could anticipate the usage of spare time for positive things/activities.

Role of Credit Rating in determining Capital structure: Evidence from Non-Financial sector of Pakistan

2020 ◽  
Vol 38 (3) ◽  
Author(s):  
Shoaib Ali ◽  
Imran Yousaf ◽  
Muhammad Naveed
Keyword(s):  
Capital Structure ◽  
Credit Rating ◽  
Least Square ◽  
Annual Data ◽  
Leverage Ratio ◽  
Financial Decisions ◽  
Financial Firms ◽  
High Level ◽  
The Impact ◽  
The Capital Structure

This paper aims to examine the impact of external credit ratings on the financial decisions of the firms in Pakistan.  This study uses the annual data of 70 non-financial firms for the period 2012-2018. It uses ordinary least square (OLS) to estimate the impact of credit rating on capital structure. The results show that rated firm has a high level of leverage. Moreover, Profitability and tanagability are also found to be a significantly negative determinant of the capital structure, whereas, size of the firm has a significant positive relationship with the capital structure of the firm.  Besides, there exists a non-linear relationship between the credit rating and the capital structure. The rated firms have higher leverage as compared to the non-rated firms. The high and low rated firms have a low level of leverage, while mid rated firms have a higher leverage ratio. The finding of the study have practical implications for the manager; they can have easier access to the financial market by just having a credit rating no matter high or low. Policymakers must stress upon the rating agencies to keep improving themselves as their rating severs as the measure to judge the creditworthiness of the firm by both the investors and management as well.

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