scholarly journals The CRISPR-Cas System and its Relationship with MGEs in Klebsiella

2021 ◽  
Author(s):  
Daofeng Qu ◽  
Yuqiao Zhou ◽  
Wei Zhou ◽  
Jinzhi Zhou ◽  
Ze He ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Structural Characteristics ◽  
Principal Component ◽  
Mobile Genetic Elements ◽  
Whole Genome ◽  
Factors Affecting ◽  
Associated Proteins ◽  
Immunological System ◽  
Cas Gene

Abstract Microorganisms have developed many strategies in the process of long-term defense against external attacks, one of which is the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas) bacterial immunological system. In this paper, the whole genome of 300 strains of Klebsiella was collected, the CRISPR-Cas system in the strains was statistically analyzed, and the types and structures of CRISPR system in Klebsiella were explored, as well as the correlation between CRISPR and mobile genetic elements (MGEs). Through principal component analysis (PCA), we found that Cas gene, plasmids, integron, IS1, IS609 and DNA-related enzymes were closely related to CRISPR. Compared the structural characteristics of plasmids, the DinG family helicases, Cas6, Csf2, and IS5 were observed near the CRISPR loci in plasmid, which is also confirmed by the the results of PCA that they may be important factors affecting the plasmid whith CRISPR.

Reliability Parameters Forecasting for Transmission Lines Based on Principal Component Regression

2013 ◽  
Vol 291-294 ◽  
pp. 2381-2386 ◽  
Author(s):  
Wen Xia Liu ◽  
Ji Kai Xu ◽  
Hong Yuan Jiang ◽  
Yong Tao Shen
Keyword(s):  
Principal Component Analysis ◽  
Transmission Lines ◽  
Principal Component Regression ◽  
Principal Component ◽  
Forecasting Accuracy ◽  
Factors Affecting ◽  
Reliability Parameters ◽  
Impacting Factors ◽  
Simulation Results

It is the foundation for evaluating the reliability of transmission lines to obtain and analyze the original reliability parameters. However, these parameters depend on long- term statistic and calculation. In the case of lacking such parameters in a new project , this paper proposes a method of Principal Component Analysis to obtain the principal component of the impacting factors ,in which various factors affecting reliability parameters are taken into account. Through this method, we can use PCR to obtain the failure rate of the unknown transmission lines on the base of the known credible lines’ rates. The simulation results show that the proposed approach possesses higher forecasting accuracy and provides references for the power system dispatching departments and transmission lines maintenance departments.

scholarly journals Research on key influence factors of creativity development of applied undergraduates based on PCA

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiangmin Ren ◽  
Jingwei Yu
Keyword(s):  
Principal Component Analysis ◽  
Influence Factors ◽  
Principal Component ◽  
Heilongjiang Province ◽  
Key Factors ◽  
Factors Affecting ◽  
The Core ◽  
Creativity Development ◽  
Teachers And Students ◽  
Core Characteristics

Abstract Creativity is one of the core characteristics of talent; for this reason, the creativity development of applied undergraduates should be one of the basic components of their education. This article gives an overview of the meaning of the creativity of applied undergraduates and makes a literature knowledge-mining and expert investigation on the factors affecting the creativity development. We obtained more than 100 influencing factors, filtered out the duplicative factors, and formed the remaining factors into a questionnaire. A survey was conducted among 1460 teachers and students of some applied undergraduates in Heilongjiang Province. By using principal component analysis (PCA) to analyse the questionnaire, the key factors that affect the creativity development of applied undergraduates are obtained, and the key factors are systematically analysed. According to the results of the analysis, the specific ways and methods of the creativity development of applied undergraduates are put forward.

scholarly journals Bidimensional and Multidimensional Principal Component Analysis in Long Term Atmospheric Monitoring

Atmosphere ◽  
2016 ◽  
Vol 7 (12) ◽  
pp. 155 ◽  
Author(s):  
Barbara Giussani ◽  
Simone Roncoroni ◽  
Sandro Recchia ◽  
Andrea Pozzi
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Atmospheric Monitoring

scholarly journals Diversity of entomopathogenic fungi associated with Mediterranean fruit fly (Ceratitis capitata (Diptera: Tephritidae)) in Moroccan Argan forests and nearby area: impact of soil factors on their distribution

BMC Ecology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ayoub Hallouti ◽  
Mohamed Ait Hamza ◽  
Abdelaziz Zahidi ◽  
Rachid Ait Hammou ◽  
Rachid Bouharroud ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Entomopathogenic Fungi ◽  
Ceratitis Capitata ◽  
Chemical Properties ◽  
Principal Component ◽  
Fruit Fly ◽  
Component Analysis ◽  
Organic Content ◽  
Pathogenicity Test ◽  
Factors Affecting

Abstract Background Studying the ecology of biocontrol-agents is a prerequisite to effectively control medfly (Ceratitis capitata (Diptera: Tephritidae)) with entomopathogenic fungi. In this context, factors affecting the occurrence and distribution of medfly-associated entomopathogenic-fungi were studied. Soil samples (22) were collected from natural and cultivated areas of Souss-region Morocco. Results A total of 260 fungal isolates belonging to 22 species and 10 genera were obtained by using medfly pupae as bait. Medfly-associated fungi were detected in all studied soils and pupae infection percentages ranged from 3.33% to 48%. Two genera, Fusarium and Beauveria were the most frequent with 83 isolates (32%) and 50 isolates (19.23%) respectively. Pathogenicity test of isolated species against medfly pupae showed high mortality rates up to 91% for some strains. Principal component analysis (PCA) demonstrated a strong influence of origin, physical, and chemical properties of soil on the abundance of these fungi. In general, medfly-associated fungi were more abundant in soils with moderate pH (7.5 to 8) having high sand and organic content. High relative humidity negatively influenced the abundance of these fungi. Both factors directly affected the fungal infection percentages in pupae. The response of fungi to these parameters varied among species. According to principal component analysis (PCA), the soils of argan fields and forests were more suitable for the development of medfly-associated fungi than citrus orchards. Conclusions These results guide identifying suitable soils for the effective application of entomopathogenic fungi as biological control agents. In summary, isolated indigenous strains seem to be a promising option to control C. capitata.

Long-term runoff forecast using BP neural network based on climatic factors and mutual information method in the Qujiang Catchment of China

2020 ◽  
Author(s):  
Huihui Dai
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Mutual Information ◽  
Bp Neural Network ◽  
Climatic Factors ◽  
Principal Component ◽  
Component Analysis ◽  
Information Method ◽  
Runoff Forecast

<p>The formation of runoff is extremely complicated, and it is not good enough to forecast the future runoff only by using the previous runoff or meteorological data. In order to improve the forecast precision of the medium and long-term runoff forecast model, a set of forecast factor group is selected from meteorological factors, such as rainfall, temperature, air pressure and the circulation factors released by the National Meteorological Center  using the method of mutual information and principal component analysis respectively. Results of the forecast in the Qujiang Catchment suggest the climatic factor-based BP neural network hydrological forecasting model has a better forecasting effect using the mutual information method than using the principal component analysis method.</p>

scholarly journals Forcing variables in simulation of transpiration of water stressed plants determined by principal component analysis

2016 ◽  
Vol 30 (4) ◽  
pp. 431-445
Author(s):  
Angelica Durigon ◽  
Quirijn de Jong van Lier ◽  
Klaas Metselaar
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Specific Humidity ◽  
Leaf Angle ◽  
Prediction Errors ◽  
Angle Distribution ◽  
Time Frequency ◽  
Soil Dryness

AbstractTo date, measuring plant transpiration at canopy scale is laborious and its estimation by numerical modelling can be used to assess high time frequency data. When using the model by Jacobs (1994) to simulate transpiration of water stressed plants it needs to be reparametrized. We compare the importance of model variables affecting simulated transpiration of water stressed plants. A systematic literature review was performed to recover existing parameterizations to be tested in the model. Data from a field experiment with common bean under full and deficit irrigation were used to correlate estimations to forcing variables applying principal component analysis. New parameterizations resulted in a moderate reduction of prediction errors and in an increase in model performance. Agsmodel was sensitive to changes in the mesophyll conductance and leaf angle distribution parameterizations, allowing model improvement. Simulated transpiration could be separated in temporal components. Daily, afternoon depression and long-term components for the fully irrigated treatment were more related to atmospheric forcing variables (specific humidity deficit between stomata and air, relative air humidity and canopy temperature). Daily and afternoon depression components for the deficit-irrigated treatment were related to both atmospheric and soil dryness, and long-term component was related to soil dryness.

Principal Component Analysis the Economy of Shanghai in 2010

2011 ◽  
Vol 50-51 ◽  
pp. 404-408
Author(s):  
Xiao Qiang Guo ◽  
Zhen Dong Li ◽  
Dong Dong Hao ◽  
Xin Xie ◽  
Jian Min Wang
Keyword(s):  
Principal Component Analysis ◽  
Economic Development ◽  
Principal Component ◽  
Component Analysis ◽  
Evaluation Index ◽  
Short Term ◽  
Construction Costs ◽  
World Expo ◽  
Shanghai World Expo

This paper from the economic analysis, quantitative evaluation of the 2010 Shanghai World Exop impact. First, from the short-term and long-term benefits of the two considerations, the loss of earnings, base construction costs on the percentage of total funding, permanent building retained, the number of daily tours, the number of participating countries for the evaluation index, subjectively weight to the five indicators，calculate its scores to rank for five World Expos including Shanghai World Expo. Second, using principal component analysis, we get the five indicators of objective weighting and ranking for above five World Expos. The results show that the Shanghai World Expo will boost the economic development and has a huge influence on the economy

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